Quick Start Guide
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Quick Start Guide | Contents | 2
Contents
Introduction.................................................................................................. 3
How to Use the 1010data Graphical User Interface................................. 4
How to Select Rows.................................................................................. 11
How to Create a Computed Column........................................................17
Summarizing Data in 1010data: Tabulation............................................ 21
How to Link Tables................................................................................... 25
Summarizing Data in 1010data: Cross-Tabulation................................. 29
How to Save a Quick Query..................................................................... 36
How to Share Quick Queries and Folders.............................................. 48
©
2014 1010data, Inc. All rights reserved.
Quick Start Guide | Introduction | 3
Introduction
The most difficult part of using any new computing tool comes the first time you sit down in front of it and
inevitably ask yourself, "Now what do I do?" Well if that's how you felt the first time you looked at the
1010data interface, you've come to the right place. After all, you're dealing with data. A lot of data. And you
can see ALL of it. Most people have never had that experience. Count yourself lucky. With this Quick Start
Guide, you'll learn all the basics that will help you understand how 1010data works and why it's different
from other database solutions.
Quick Start Guide | How to Use the 1010data Graphical User Interface | 4
How to Use the 1010data Graphical User Interface
1010data gives you several options to interact with the system and analyze your data, but when you first
get started you're most likely going to spend most of your time in the Graphical User Interface (GUI). This
is a good thing. The 1010data GUI is a browser-based interface that works a lot like many spreadsheet
applications, such as MS Excel. It uses many elements you may already be familiar with, such as folders,
navigation buttons and menus. This tutorial will walk you through the major elements found in the 1010data
GUI.
To get started, the first thing you need to do is login to the system. You can do this by going to our main
website and entering your username and password into the provided fields at the top of the page. You can
also go to 1010data.com where you'll see this screen:
Enter your 1010data username and password in the designated fields above. Then, click the Login button.
Logging in may take a few seconds.
Note: If you forgot your password, click the Forgot Your Password? link (circled in red above).
When you've logged in you'll arrive at the Start Page:
Upon logging in, the folders and tables visible to you appear in a collapsible section on the left-hand side
of the browser window. Once you're at the Start Page you can open tables contained in the folders, or you
can re-open Recent Worksheets. To open a Recent Worksheet, just click on one of the links in the upperright-hand pane shown above.
Note: If it's your first time logging into the system, you won't have any worksheets listed in the
Recent Worksheets section.
A worksheet is a working copy of a table. When you open a table in the spreadsheet interface it becomes
a "worksheet." In worksheets, you can work with and manipulate your data. A table is the permanent,
unchanging version of the data that is saved on the server. If you save a worksheet permanently, and it
becomes a "table." Or, as you'll learn later, you can simply save your analysis of a worksheet so you can
apply it to the table any time you like.
Quick Start Guide | How to Use the 1010data Graphical User Interface | 5
To open a saved table, use the folders in the left-hand pane shown above. To see what's in a folder, you
can double-click on it, or single-click the arrow to its immediate left. When a folder is open you will see the
folders and tables contained within it, as follows:
In the screenshot above, the red box outlines the folders and tables contained in the Training Examples
folder. You can also see that the retail folder is open, and in it is a table called Sales Item Detail. To open
a table, simply double-click on it. Throughout this tutorial, we'll use the Sales Item Detail and Product
Master tables to illustrate concepts like Selecting Rows and Linking Tables and Worksheets.
Now that we know how to open tables into worksheets we'll take a look at how to use the spreadsheet
interface to work with data. The Sales Item Detail table we have open looks like this:
Quick Start Guide | How to Use the 1010data Graphical User Interface | 6
This is the basic view of a data table in 1010data. At the top of the screen, outlined by the red rectangle,
are the Back and Forward buttons. Use these buttons when you want to undo or redo one of your actions.
To the immediate right of those buttons is the current path to the table in which you are currently working.
Note: If you click on any of the parts of the Path that worksheet will be opened in the in the Folder
Browser.
Underneath the Back/Forward buttons are the menus. We'll cover these in more depth throughout this
guide. For now, just keep in mind that a lot of the actions you can perform on your data can be done via the
menus at the top of your browser's window. The table below provides a description of each menu and its
available options:
Table 1: 1010data GUI Menus
1010data GUI Menu
Menu Description
File
Options for opening, closing and saving common
1010data tools such as Worksheets, Macros and
Queries.
View
Options for how your 1010data GUI appears. You
can set your view preferences here.
Actions
Options to Do, Undo and Edit actions in 1010data
such as row selections and sorts.
Quick Start Guide | How to Use the 1010data Graphical User Interface | 7
1010data GUI Menu
Menu Description
Columns
Options for working with columns. You can go to a
specific column, create computed columns and link
other tables and worksheets to your current table
here.
Rows
Options for interacting with Rows in your current
table. You can go to a specific row, find rows and
select rows here.
Analysis
Quick access to Summaries, Tabulations and
Cross-Tabulations.
Download
Download options to save your data locally in a
variety of file types such as Excel, CSV ad XML.
Reports
Options for report creation.
Help
Options for support. Also grants access to the
1010data General Help, a detailed reference
document on all the functionality of 1010data.
Finally, surrounded by the red oval in the previous screenshot, are the Up button, Down button and the ?
button. When you click the Up/Down buttons 1010data will sort the data for the entire table based on the
column of the Up or Down button you clicked.
Note: While we'll get into a deeper explanation later in this guide, don't sort your tables unless
you've narrowed your data down to a manageable size. It's always better to narrow your data down
before performing a sort. Sorting is very system resource intensive. Instead of sorting, try first
performing a tabulation or selecting a narrow range of rows.
The ? button is very useful and gives you lots of information about the column you're working in. If you click
the ? button for the Sales column, this is what you'll see:
Quick Start Guide | How to Use the 1010data Graphical User Interface | 8
As you can see, clicking the ? button at the top of a column provides you with a considerable amount of
useful information. You can use it in your analyses of your data, especially in places like writing macro
language queries. We won't delve into these topics just yet, but if you find yourself in a position where you
need information about a column you're working with, this is an excellent place to start.
Let's go back to our Sales Item Detail table. Outlined on in red on the right-hand side is the Scroll bar:
Quick Start Guide | How to Use the 1010data Graphical User Interface | 9
The Scroll bars in 1010data allow you to navigate through your data row by row. For the purposes of this
tutorial, we created a very small dataset to illustrate the concepts we're working with. In this instance,
you can scroll through your data in just a few seconds. However, in practice your tables can be billions of
rows long. As you work with the system, keep in mind that scrolling isn't the most effective way to get to a
particular section of data. For that, the best method is to use the Select Rows option, which we'll cover in
detail in the next tutorial of this guide. The following table provides a short description of each button in the
scroll bar:
Table 2: Scroll Buttons
Scroll Button
Description
Moves the visible rows of data in a table down by
one row.
Moves the visible rows of data in a table down by
an entire page. In other words, the first non-visible
row in the table becomes the first visible row after
clicking.
Jumps down to the very end of the table.
Note: Clicking in the light-gray area of the scroll bar doesn't produce any results. Clicking in the
dark gray area moves the table down to proportionally to the area clicked.
Quick Start Guide | How to Use the 1010data Graphical User Interface | 10
The last thing we'll look at for this tutorial is how to arrange and re-arrange your columns. First, click
the Column menu, then Rearrange Columns... as follow, which will launch the Select and Rearrange
Columns dialog, also shown below:
As you can see in the screenshot, on the left is the Available Columns list, which shows all the columns
contained in your data table, whether they currently show in your browser or not. On the right is the
Displayed Columns list, which only shows the columns of your table currently visible in the 1010data GUI.
This is how you control the order in which the columns in your table appear left to right. To change the
order of the columns, select the column you want to move in the Available Columns list, then select the
column you'd like it to appear after in the Displayed Columns list. Then click the Show After >>> button.
Take a little time to familiarize yourself with the basics menus and options in 1010data. Make sure you are
comfortable opening a table, and don't be afraid to customize the table by rearranging columns so that
they're in an order that's useful to you. This will make the next few tutorials much easier, and allow you to
focus on the new material presented in them. Before you know it, you'll be performing custom analysis on
your data!
Quick Start Guide | How to Select Rows | 11
How to Select Rows
One of the most basic tasks in 1010data is to take a large body of data and reduce it to a smaller dataset
that contains more specific information. The 1010data spreadsheet interface makes this easy to do. While
there are many ways to manipulate your data, the most basic is a Row Selection. Let's start there.
In our example, we're using a set of data called Sales Item Detail, which contains 35 rows of data, of
which only the first 32 are displayed (11 in the screenshot below).
Now, when you work with real data sets for analysis there will, of course, be a lot more of it. However, for
this tutorial, we think you'll appreciate the instant gratification that comes with seeing the results of your
actions immediately. This is just a little easier with a small table, so we've created one for this guide.
Whether you're working with a table that is very small or very large, the first step to answering your
questions is to narrow down the data in the worksheet so you can only see the pieces of information that
apply to your question(s). Let's take a look at the first step of a Row Selection:
To get started, click the Rows menu underneath your browser's address bar. Then, click Select Rows...
Quick Start Guide | How to Select Rows | 12
When you click the Select Rows... option on the menu, the Select Rows dialog will appear in your
browser:
Let's take a minute to think about the real purpose of Row Selection. The goal here is to go from a large
collection of general data to a smaller collection of data specific to the question being asked. One question
might be, "Which store in our chain had the highest sales in December?" Another could be, "What were
the highest and lowest sales figures for a single transaction?" In both these cases, we start with all of our
data and aim to learn more about a question that only requires a subset of that data to answer. As we will
see, sometimes we want to provide numerous criteria to narrow down the dataset as much as possible.
However, when working with Row Selection in 1010data, there one really important guideline you should
follow whenever possible:
•
Always make the selection that will eliminate the largest chunk of data first
This almost always means you should select a date range first.
Quick Start Guide | How to Select Rows | 13
When you work with very large datasets like those in 1010data, the order in which you perform your
operations on the data makes a difference in how fast the system can complete the operations you asked
it to. If you make the largest selection (i.e., the selection that will eliminate the most data) first, then all
the subsequent selections you perform will finish faster because they don't have to work with as much
data. Now, the situation will sometimes dictate what the largest selection you can make is. But, as a rule
of thumb, if your data has a date or time associated with it, that's the best place to start. Let's take a quick
look at how to perform a selection based on a date range.
First, make sure you have the Select Rows dialog open as shown below. Now, find the field that contains
a drop-down menu next to the words, "is between," as in the next screenshot.
Click the drop-down list and select the Date value. Next, we'll enter the dates. The dates in our table
range from 5/15/2012 to 6/19/2012. Enter any two dates that interest you, so long as they're actually in the
dataset and the earlier date comes first, as seen here:
Note: The is between operator for the dates shown above is inclusive, meaning it includes the
dates entered in the fields. To the computer this means its using >= and <= operators, not > and <.
You might have also noticed that we used different date formats in each box. That's to illustrate that both
these formats are valid in 1010data, so use whichever you're comfortable with.
Once you've entered the information, click the Select button. Your results should appear as follows:
Quick Start Guide | How to Select Rows | 14
Congratulations, you've just performed your first analysis in 1010data! As you can see in the screen above,
we've cut the amount of data in our table by half.
Next, we'd like to gain some insight into how individual stores are performing, so we give the Selection
Tool some additional information. In this case, we have to give it a store number, and let it know that
we only want to see rows that contain the store number we're interested in. We do this by providing a
comparison criterion. We've done this in the screenshot below:
Quick Start Guide | How to Select Rows | 15
As you can see, we've given the Selection Tool a store number, and the comparison criterion, has the
value(s). This tells the Selection Tool that we only want to see rows from store 2. Had we selected the
second comparison option, does not have the value(s), we would see all the stores on the table except 2.
If you want to include more than one value (i.e., more than a single store in the above example), you can
do so by simply separating the values with a space, as follows:
This selection will produce results from both stores 1 and 3. This feature can come in handy when working
with things like product numbers.
Now that we've given the Selection Tool all the information it needs for the results we want, click the Select
button. Your results will appear soon after, as shown below:
In just a few minutes, we've narrowed down our data from 32 rows all the way to 5. That's less than onesixth the original data. Also, note that the new table shows you what selections you've already performed
(encircled by a thin red line), so you can move forward with additional selections without duplicating your
efforts.
There is another very useful trick to know that will help you perform basic row selections quickly. You
can right-click on any cell of any row in a table and choose from several pre-built selection options. For
instance, if we right-click on the Date value for a row, the following menu appears:
By using the right-click option on a Date cell in this table we can easily choose from several row selection
options pertain to Date. Now let's look at the option if we right-click on an account cell:
Quick Start Guide | How to Select Rows | 16
In this example we used the right-click option on an Account cell, and the options presented to use all
select rows based on Account and not Date. If you don't need to perform a compound selection this is a
great way to quickly select the rows you're interested in.
Row Selection is an incredibly powerful tool when working with large datasets. Using this simple method,
you will be able to eliminate huge chunks of data and focus on what really matters for your analytical
needs. Of course, you can use the advanced selection features to narrow down your results even more,
but that's a topic for another tutorial. If you're so inclined, make up a few Row Selections of your own and
try them out on our sample data. It will make a big difference as you learn how to work with 1010data's
spreadsheet interface, and ultimately, we hope, make your analysis faster and more accurate. Good luck!
Quick Start Guide | How to Create a Computed Column | 17
How to Create a Computed Column
One of the most basic and useful analytical tools in 1010data is the Computed Column. Computed
Columns are columns you create yourself using information that's already in the table you're working with.
For example, suppose you have a table that contains all the sales data for a chain of stores. This table has
one column called Sales, which is the purchase price paid by the customer. It has another column called
Cost, which is the cost of the item to the retailer. With a Computed Column it is easy to create a third
column called, "Margin," that will contain the difference between the Sale Price and the Cost. Fortunately,
we happen to have such a table right here to show you what we mean. So let's walk through creating a
"Margin," column together.
Below is a screenshot of the first row of data in our table with all the column names at the top. These
names indicate the data presented in the table:
In the next screenshot, we have an image of the two columns we'll use to create our Margin column, in the
1010data user interface:
Next, we'll use the web-based interface of 1010data to create a computed column. Complete the following
steps:
Locate the Columns menu at the top of the table and click: Columns > Create Computed Column...
You can see where this is located in the next screenshot:
Quick Start Guide | How to Create a Computed Column | 18
If you followed the previous step correctly, the Create Computed Column dialog will appear as shown
below:
Now that we have our dialog the real fun begins. Let's look at each of the 6 fields you can use to define a
Computed Column, one by one.
Table 3: Computed Column Dialog Fields
Field Name
Explanation
Required?
Column Name
The column name is the name the computer uses when
working with the column. The column name must be all lowercase letters and cannot contain any spaces or numbers. You
will use this name for writing value expressions and queries as
a more advanced user (a small introduction to this will come in
this tutorial).
Yes
Column Heading
This is the "plain English" name for the column that appears in
the interface. This name can have capital letters and spaces.
No
(Recommended)
Value Expression This is where you type the formula that calculates the new
Computed Column.
Yes
Display Format
No
This tells the 1010data environment how to display the new
number in your Computed Column (i.e., a date, a number,
text...etc.).
Note: This
can usually
be left as
Quick Start Guide | How to Create a Computed Column | 19
Field Name
Explanation
Required?
the default
value
Column Width
Decimal Places
This tells 1010data how many place values to hold in the
column (or how many characters in its text).
No
This tells 1010data how many values after the decimal place
it should display. In this tutorial we're working with a dollar
amount, so 2 would be the appropriate entry most of the time.
However, as you explore 1010data and Computed Columns,
you may run into situations where you need more, or none at
all.
No
Note: This
can usually
be left as
the default
value
Note: This
can usually
be left as
the default
value
Now that we know what each of the fields in the Create Computed Column dialog represents, let's take a
look at how we fill those in:
In the screenshot above, we've filled in the columns with the following values, from top to bottom:
1.
2.
3.
4.
Column Name: margin
Column Heading: Margin
Value Expression: sales-cost (more on this below)
Display Format: Number (with commas)
Quick Start Guide | How to Create a Computed Column | 20
5. Column Width: 5 (5 numerical digits in this case)
6. Decimal Places: 2
Let's briefly discuss the value of the Value Expression box. For this field, we entered:
sales - cost
What does this mean exactly? In 1010data, Value Expressions are calculations that you create which help
you analyze your data. You can write Value Expressions that perform many simple and advanced kinds of
calculations. You can even perform a series of actions by writing a string of expressions called a query.
If you looked at the screenshot above carefully you might have noticed the small table at the bottom of our
Create Computed Column dialog. You can find out the Column Name of the columns in this table. It is
important to remember when writing Value Expressions to always use the Column Name, not the Column
Heading.
What is actually happening, if we put it in plain English, is: "I am creating a new column called "margin."
The "margin" column is the value of the "sales" column minus the value of the "cost" column. All that is
left to do is click the Submit button at the top of the dialog. 1010data does the rest. Our results are in the
screenshot below:
And there we have it. We created a new column in the table with a very small amount of effort. The values
in each row are populated by the equation we entered as our Value Expression, and we can now easily
see the margin for every item sold in the entire table. Of course, Computed Columns are much more
powerful than merely subtracting or adding one column from another. With a little practice, you'll be able to
build columns based on more complicated equations, such as Standard Deviations and Sharpe Ratios. If
you'd like to know more about Computed Columns and Value Expressions, you can also visit our General
Help section, which contains a wealth of knowledge on everything 1010data. We hope you found this
tutorial helpful. Now get out there and practice!
Quick Start Guide | Summarizing Data in 1010data: Tabulation | 21
Summarizing Data in 1010data: Tabulation
Another basic, yet powerful, analysis tool provided in 1010data is the Tabulation. A tabulation is a handy
way to summarize large amounts of data into a small, easy-to-read table. Tabulations are a great place to
start when you want to get a feel for what all those billions of rows of data in your table really mean.
Let's start with a basic example. We'll start again with a Sales Item Detail table that has records for every
transaction at every store in our fictional chain of stores. Our first tabulation will simply show each of the
three stores in our chain and the total sales for each store. Let's get started.
First, let's open the Tabulation tool in 1010data. Make sure you are logged into your account. Then, open a
table of sample data. Finally, click the Analysis menu, and then click Tabulation, as shown below:
This will launch the Tabulation dialog, which should look like the following screenshot:
Now, let's walk through each of the components of the dialog, step by step.
The first thing you should do is give your tabulation a title. While it's not required to give your tabulation
a title, it is a good way to remind yourself what information is held in a tablulation after you've saved it.
The next step is to choose the column we'd like to group the information by. Essentially, how do we want
to subtotal the data. Remember, we're keeping things simple for our first tabulation. The first question
we should ask is, "What values do we want to use to group the records?" Since we want to see one row
for each store with sales summarized, choose Store in the Column drop-down menu. We also have to
choose the way we'd like to sort the group (the stores), so let's choose Up in the Sort drop-down menu.
Quick Start Guide | Summarizing Data in 1010data: Tabulation | 22
Before we move on, let's take a minute to make sure we understand grouping in the context of a tabulation.
After we finish configuring our tabulation, we will see a brand new table. On this new table, we only want
to see one row for each store in our chain, so we will group by store. Grouping is a way of pooling all the
records for a single entity, in this case a store, into a single entry in the table. Later, we'll also group the
data by the transaction ID.
Now that we've decided how to group our data, let's summarize a different piece of data. Since we set out
with the goal of seeing the total sales for each store, we'll summarize the Sales column. Under the section
of the Tabulation dialog that says, "Which columns' data would you like to summarize? (Optional), select
Sales from the Column drop-down menu. And since we want to see the total dollar amount for sales at
each store in our imaginary chain, we'll select the sum from the Type of Summary drop-down menu.
Note: Leave the Reference Column value blank. It is used for advanced summarization functions,
such as weighted averages.
Once you've selected the data you want to group by and the data you want to summarize, it's time to
generate the tabulation. Simply click the Submit button at the top of the dialog. Your results will appear
shortly after you submit. You should see something that looks like the screenshot below:
If your results look like the table in the screenshot above, Congratulations! You've just summarized your
data. Notice that there is a row of data in gray at the top of the table. This row shows the totals for each
column of data being summarized. As you can see, our three fictional stores generated $59.85 in sales
with Store 1 generating $23.19, Store 2 generating $16.31 and Store 3 generating $20.35. While this
might not seem like a terribly useful thing for a chain of three stores, it becomes much more useful when
summarizing chains with hundreds, or even thousands, of stores. Now, let's take a look at a slightly more
complex example of tabulation. Click the Back button in 1010data to return to your original table, and then
re-open the Tabulation dialog just as we did before. Take a look at the next screenshot and see if you can
understand why we've made the decisions the way we have.
Quick Start Guide | Summarizing Data in 1010data: Tabulation | 23
Instead of looking at the total sales per store, we're going to look at sales totals for each transaction in
our base table. However, we'd also like to know at which store any given transaction took place. Just as
before, we'll start by selecting a column with which we can group our data. In this case, we'd like to see the
total sales figures for each transaction, so we'll group by Transaction ID. However, we also want to know
which store recorded each of the transactions in our table, so we'll also group by the Store. Note that the
order in which you choose the group by data is critical.
Now that we have decided how to group our data, first by Transaction, then by Store, we can choose the
data we want to summarize. In this example, we are still summarizing sales by dollar totals, so we can
make the same exact selection we made in the last example.
Just as in the last example, when you have set all the options in the dialog correctly, simply click the
Submit button at the top of the dialog to generate your results. When the new worksheet is generated, it
should look something like the next screenshot:
Quick Start Guide | Summarizing Data in 1010data: Tabulation | 24
Notice that in the new summary we generated, the total sales figure at the top of the table remains
the same. However, instead of the total sales by store, we can now see the total sales figure for each
transaction AND the store at which the transaction took place. This gives us an extra layer of detail, or
granularity, in our results. Yet, the new table is still much easier to parse than our original base table.
The final step in our tutorial will show you how to download your results into MS Excel once you've finished
your tabulation. Simply follow these steps to import your results to Excel:
1. On the 1010data menu bar, click the Download menu, then click MS Excel.
Once you are comfortable with them, Tabulations in 1010data are a very fast and powerful way to get a
sense of what information your data contains and how it can be leveraged to make decisions. So with that
in mind, good luck and keep practicing.
Quick Start Guide | How to Link Tables | 25
How to Link Tables
When you work a lot with data you will often find yourself in a position where you want to use two separate
tables that contain different but related data to answer a question. The Sales Item Detail table we've
been working with in the previous tutorials of this guide contains information about every transaction
for our fictitious retail chain. But what if you wanted to know which departments each item from those
transactions came from? What if you want to know more about the Account the transaction came from? In
each case, a different table exists that contains more information about these areas of interest, and if we
could combine one of those tables, the Product Master table and Account Master table respectively, and
match up the data from one of those tables with our Sales Item Detail table, you'd be able to learn exactly
what those details are. 1010data has a powerful and highly-effective tool that makes incorporating related
data tables with each other both simple and straight-forward. It's called Linking, and it's one of the things
1010data does best.
To give this some context let's work through an example. We'll start with our now familiar Sales Item
Detail table. Just as a refresher, here's what it looks like:
This table contains lots of useful information about every transaction that's happened in our fictional retail
POS system over the past few days. Because we have transaction detail table, we have a row for each
item in a transaction, not just summarized totals. The Item SKU column gives a reference describing the
exact product that was purchased. So with this table we can clearly see the date, store and sale price of
every item we've sold, as well as the transaction in which it took place. But we have a problem. We don't
know, based on the information in this table, what any of the items actually were. All we have is an SKU
code, which might mean something to the computer, but to humans it's all but meaningless.
Quick Start Guide | How to Link Tables | 26
Fortunately, we do have access to another table that gives us a description of these items. Let's take a
look at our Product Master table:
Above is the Product Master table. It contains specific information of all the product SKUs that are also
in our Sales Item Detail table. Here we can see descriptions for the products, their category, and the
department of our fictitious retail chain that sells each. But what if we wanted to look at this information as it
relates to our sales data? The answer, of course, is to link the two tables together at a common data point.
In this instance, both tables contain Item SKU data, so let's take a look at the process for linking the tables
there.
Note: Just in case you're coming to 1010data with an SQL background, you can think of linking
tables as equivalent to a join in SQL.
Start by making sure you have the Sales Item Detail table open, then click Columns > Link in Another
Table.... This will start the Link in Another Table dialog, shown below:
The first decision you have to make in the dialog is to select the table you will link to the current table. The
dialog has your current folder open by default, which is where our Product Master table is. Click the link to
the Product Master table and you'll see next step of the dialog:
Quick Start Guide | How to Link Tables | 27
Above is the Step 2: Select columns dialog. In this dialog you are asked to select at least one column in
the new table that matches one from the table we originally opened. As an example, an item in the Sales
Item Detail table that has an Item SKU of 472192 will match with the first row in the Product Master
Table that also has a SKU of 472192 . These shared columns provide a common data point where the two
tables can be linked. While you can link two tables at more than one column at the same time, we'll stick to
linking at a single column for the purposes of this tutorial.
Note: When finding columns that match in order to Link a table, make sure that the columns from
both tables have the same data type. For example, if you had one column with integer values in
one table and a column with character or string values in the other, you'd get an error if you tried to
link the tables with those columns.
First, select the column where the tables will be linked for the table you currently have open. In the
example above, the column selected is Item SKU. It's important to note here that the items in each dropdown lists are labeled with their Column Heading, not the Column Name.
Next, it's time to select a column in the table we're linking in that corresponds to the one we specified in the
first table. In this case, it's the SKU column. Again, this is the heading of the column, not the name.
Finally, in the section outlined by the green circle (pictured above), we provide a suffix for the new columns
we're adding to the existing table. This is necessary because the two tables we're merging have very
similar column labels. By adding the suffix, "PM" to the columns from the Product Master table, it will be
clear in the final worksheet which columns came from the Sales Item Detail table and which came from
the Product Master table. Now that we've provided the system with all the information it needs, click the
Finish button at the top of the dialog to view the results:
Quick Start Guide | How to Link Tables | 28
If you click on the "?" for any of the new columns in our freshly linked table, you'll see how the system
applies the suffix, as follows:
This tutorial was intended to introduce you to the topic of linking. But it's a deep topic with many variations.
Fortunately, it's also very powerful. Finding ways to combine datasets and provide them with context is
what we're all about at 1010data. Take some time to explore tables and see if they have places where they
can be joined by columns with similar information. This will help you understand how your data is interrelated, and start you down the path of deeper, more insightful analysis.
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 29
Summarizing Data in 1010data: Cross-Tabulation
Welcome back to 1010data's Quick Start Guide. By now you've learned a lot about how to interact with
1010data and use its analytics tools to work with your data. If you've come this far, you're hopefully starting
to get comfortable with basic analysis such as selecting rows and creating computed columns. You should
be able to work with our GUI, and you've linked tables together to learn more about your data and how it
affects your business. Along the way, you also learned how to summarize your data with a tabulation.
In this topic we're going to take a look at how to perform Cross-Tabulations. This is a tricky concept, rightly
reserved for the last piece of our Beginner's Guide. It's also, conveniently, one of the last things you should
do when working with your data. Cross-Tabulations are fantastic for summarizing your findings so that
others can see the conclusions you've reached. If you're a regular MS Excel user, you may notice that
Cross-Tabulations share many characteristics with pivot tables.
In this topic we'll take a look at how Cross-Tabulations differ from regular Tabulations. We'll also walk
through how to create Cross-Tabulations with your own data, step by step. Before we get into CrossTabulations, let's go through a quick refresher on standard tabulations. Below are the results from the first
tabulation we performed in our tabulation tutorial:
This result was reached simply by adding up the total sales for each store and assigning the total for each
result to a single row in the table. Another way to think about this, is we created a "bucket" for each store,
and placed the amount of each transaction in the "bucket" of the store where the transaction took place.
Keep this idea in mind, as it's helpful for understanding what cross-tabulations do.
Now let's take a look at the second set of results from our first tabulation tutorial:
In this example, instead of using the store as a bucket for the sales data we're interested in, we're using
the Transaction ID as the bucket. However, the Transaction ID by itself isn't all that interesting, so we
also included the Store where the transaction took place. And, of course, we also included the Sales data
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 30
for each transaction. Now let's take a look at virtually the same summarization, only this time in a crosstabulation:
Take a second to look at the differences between our normal Tabulation and the results of our CrossTabulation. The first thing you should notice is that there's no single column for the Store. Instead, we've
given each potential value for the Store its own column and included the sales data for each Store. This is
where the "Cross" in a Cross-Tabulation comes from.
In our first example, each column represented only a single potential value related to the Transaction ID. In
other words, the results were one-dimensional. In a cross-tabulation, we have two-dimensional results. We
have produced Sum of Sales data related to the Transaction ID on the X axis, as well as Sum of Sales
data related to each individual Store on the Y axis. This is a slightly tricky concept to understand, but with
a little practice it will make sense. Let's take a look at how we produced these results:
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 31
For the purposes of this introductory tutorial, there are only four fields on which we need to focus:
•
•
•
Rows of Results (Circled in Red): This drop-down menu selects the data that will make up the rows of
your cross-tabulation. Another way to look at it, is this produces the first column of the cross-tabulation
table. In most cases, this should be the data column with the most values (unique or otherwise). For
example, with 50 stores and 10 products (or however many are in the data), the stores should be down
the rows. In the above example, we are looking at the sales per transaction. Another interesting value
for this drop-down might be the Account option, so we can look at total sales per unique customer.
Columns of Result (Circled in Green): This turns the specified column into an array of columns
of individual values. The value you select in this drop-down should have a limited number of unique
values.
What summary data would you like to see? (Circled in Blue):
•
•
Column: This drop-down menu selects the data you would like summarized. As we have throughout
this group of tutorials, we are summarizing Sales data in this example. As another example, we
might consider summarizing the Cost of each transaction. We could also create a computed column
that calculates the margin (as we did in our computed column tutorial) and summarize the margin
data.
Type of Summary: This drop-down selects the type of summary our cross-tabulation should display.
In this case, we are looking at sales totals, so we selected the sum option.
Now that we've outlined the basic anatomy of performing a cross-tabulation, let's go a little deeper. First,
we're going to look at why it's best to select metrics with many values for the rows and fewer for the
columns, then we'll try our hand at a new cross-tabulation that we build based on a specification.
In order to understand how to select the metrics for the rows and columns of a cross-tabulation we only
need to look at what happens when it is done incorrectly. Let's take a look at the first cross-tabulation
example if we reverse the rows and columns selections:
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 32
If you think about how cross-tabulation results have been generated so far, it shouldn't take much effort to
figure out what the results of the tabulation will look like:
Compare these results with the previous cross-tabulation and determine for yourself which is easier to
read. While there is nothing to stop you from doing it this way in 1010data, the correct way to perform
tabulations is fairly clear. Imagine if we decided to perform a cross-tabulation in this manner in a table with
hundreds of millions of transactions (as would be the case for any large retail chain). Things would become
impossible to read very quickly.
Now that we understand a little bit more about building a cross-tabulation, let's take a look at a more useful
example. The problem with our previous example is that breaking out the stores into individual columns
doesn't actually tell use anything new at all. It simply gives us a more visual representation of what we
already knew: i.e., that each transaction happened in one store and one store only, and that the other
stores in our summary made no sales dollars on a transaction that didn't take place there. So what kind of
question will let a cross-tabulation really flex its muscle?
Let's say that we're an analyst in our fictional retail franchise, and we're curious about how transactions
break out in terms of departments within our stores. Do most transactions contain items from one
department or several? Are there specific departments that outsell the rest? A cross-tabulation is ideal for
answering questions just like these. Let's take a quick look at our Sales Item Detail table to get started:
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 33
Our next step should be to build the cross-tabulation. Unfortunately, the column we're interested in
examining, Department, isn't actually on this table. Fortunately, we have a way to bring that information
in. For the next step, we're going to Link to our Product Master table, which has a Department column.
Follow the steps in the Linking tutorial, and your results look like this:
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 34
By linking our Sales Item Detail table to our Product Master table we've created a worksheet with
more useful information than either table possessed individually. Now, we can use a cross-tabulation to
summarize the sales data by looking at the amount for each department (our array of columns) contained
in a single transaction (each row of the cross-tabulation results). Let's set it up:
Quick Start Guide | Summarizing Data in 1010data: Cross-Tabulation | 35
This is very similar to how we setup our first cross-tabulation, only this time we're selecting the
Department for our Columns of Result drop-down menu instead of the Store. Now the results:
These results give us a clear break down of how each transaction breaks out by department. As you
can see, there are five departments (circled in red at the top of the table). Each row (one is circled in
green) represents a single transaction. The left-most column is the total for each transaction, and each
subsequent column is the Sales data for each department. You can also see the subtotals for each
Department column just above the rows of Transaction ID's. Each of these subtotals can be sorted on.
This example is very instructive because it illustrates exactly what we mean by a two-dimensional
summary of the data. It also illustrates the concepts of buckets we raised earlier in this tutorial. In this
case, we created a bucket for each department and placed the appropriate portion of each transaction in
the corresponding bucket. Finally, this example shows how you can combine different analytical tools in
1010data to produce richer, more insightful results. In this example we used linking to assign the correct
information about each Department for the transactions. Only after we linked the Sales Item Detail table
to the Product Master table were we able to summarize the data with a cross-tabulation in a way that
answered our questions.
We could spend a great deal more time focusing on cross-tabulations, and finding ways to combine
different techniques to answer our data questions. In terms of analysis, effective summarization of your
data is one of the most powerful tools at your disposal for developing ideas and answering difficult
business questions. However, the best thing you can do after understanding the concepts presented in
this tutorial is put them into practice. Work with your own data and answer the questions we've asked
here. Then, start asking new questions and see if you can find ways to summarize your data that might
provide you with answers. When you use your imagination in unison with the basic concepts put forth in
this tutorial, there's really no telling what you might discover.
Quick Start Guide | How to Save a Quick Query | 36
How to Save a Quick Query
Oftentimes, you may find it helpful to save a query rather than building it from scratch every time you want
to run it. Luckily, 1010data provides an ideal solution in the form of Quick Queries. A Quick Query is an
easy way to save your query for reuse. Quick Queries can run on tables that change over time without
needing to change the query itself. Quick Queries also allow you to parameterize the query, which will give
you (and those you share the query with) options when you use the query in the future.
In our Sales Item Detail example, we can give the user the option to select any store, instead of just one
particular store, through the use of a Quick Query.
Let's start off by building a query that shows all the transactions for store 1.
Open up the original Sales Item Detail table, then click Select Rows... from the Rows menu.
The Select Rows dialog will appear in your browser. Let's fill in this dialog so that we select the rows
associated with store 1.
Select Store from the first drop-down and has the value(s) from the second drop-down, and enter 1 into
the text field on the right.
Quick Start Guide | How to Save a Quick Query | 37
Click the Select button.
Your results will appear soon after, as shown below:
Now our worksheet contains the 17 rows from the Sales Item Detail table that are from store 1.
Note: At this point, you could save the results as a permanent table (for instance, if you want to
archive the information contained in the table). This might also be useful if you know you will need
this particular table in the future and know the information in it will never change. However, in most
cases it makes more sense to save the query, so that if the raw data changes, all you need to do is
re-run the query. Also, saving a table takes up space, and each user has limited space available to
them (the only way to know you have exceeded the space is when you receive an error message
for exceeding the limit).
So, let's save the current query as a Quick Query and parameterize it so that we can specify any store, not
just store 1.
From the File menu, click Save as Quick Query...
Quick Start Guide | How to Save a Quick Query | 38
The Save As a Quick Query dialog will appear in your browser:
Under Save into folder, you can browse to the location where you’d like to save the Quick Query. You can
save items into folders with
or
after the folder name. (These correspond to the and icons,
respectively, for folders in the Folders and Tables browser.)
Note: Although you can save the Quick Query in your My Data folder, it is recommended that
you save your Quick Queries under your user folder. This is especially important if you would like
to share access to that Quick Query with other users or user groups. For instance, you cannot
create subfolders in My Data, which means you would not be able to use the inherit permissions
feature that 1010data provides with the Inherit Users checkbox. You would need to explicitly give
permission to each user for every object you want to share in your My Data folder (in our case, our
Quick Query). If that sounds a bit confusing, don't worry. We'll get to sharing Quick Queries and
folders in How to Share Quick Queries and Folders on page 48). For now, let's just focus on
saving it.
Quick Start Guide | How to Save a Quick Query | 39
Let's navigate to the location where we'd like to save our Quick Query by first clicking on the All
Databases folder and then traversing down to our user folder for this example.
Next, give the Quick Query a descriptive name so that you and others will know what it does. Enter this
name in the Title of Query text box.
Under the section labeled Query Choices, select any checkbox in the Input? column that represents
a column you want to parameterize. In our example, we will select the checkbox associated with Value
for criterion 1 in the bottom row of the table. That way, we will be able to enter any value for the store
number, not just 1.
In the User Prompt column for that row, enter a descriptive prompt for the user, so they know what
information the query needs to work. For our example, let's use Enter store number for the prompt.
When you’re done, click the Submit button. You will see a message saying the Quick Query was saved in
the folder you specified.
If you look at the Folders and Tables browser, you can see that the new Quick Query appears where we
saved it.
Quick Start Guide | How to Save a Quick Query | 40
Double-click the Quick Query to run it.
You can see that the value that we parameterized for the store number is presented with the descriptive
prompt that we specified. Let's find out what transactions were from store 3. Enter 3 in the field labeled
Enter store number:
Then, click Submit.
Your results should appear as follows:
Quick Start Guide | How to Save a Quick Query | 41
Congratulations! You've just successfully run your first Quick Query!
Note: You could run the query for more than one store by entering multiple store numbers in a
space-separated list. For example, if you wanted to see all the transactions for store 1 and store 3,
you would enter the following:
Let's see what else we can do with our Quick Query. Go back to the Folders and Tables browser.
Select the Quick Query by single-clicking it. At the top of the Folders and Tables browser (above all the
folders), you will see the name of the Quick Query (which is automatically generated by 1010data when the
Quick Query is created) and some associated actions in parentheses after the name.
View Info
If you click the view info action, you will be presented with information about the selected Quick Query:
Quick Start Guide | How to Save a Quick Query | 42
This shows such info as the title of the Quick Query (which we gave it when we created it), the name
(including the full path), the owner, and the users who have permission to use the Quick Query. (The
Users field will be more important later when we talk about sharing Quick Queries and folders.) The
References field shows the name of the table this query will be applied to. (In our example, the name of
the Sales Item Detail table is named training.retail.item.)
Click the X in the top right corner of the dialog to dismiss it.
Edit Info
If you click the edit info action associated with the Quick Query, you will be presented with a dialog to edit
all of its information.
Note: If you change the name of the table from the default system-generated name, it must not
contain any capital letters, spaces, or symbols other than underscores (_), and it must begin with a
letter.
We won't make any changes now. We'll come back to this dialog a little later. Click the X in the top right
corner of the dialog to dismiss it.
Edit Query
The edit query action allows you to relaunch the Save As a Quick Query dialog and make changes to it.
Quick Start Guide | How to Save a Quick Query | 43
Let's explore this a little bit.
Say we want to have a little more flexibility with our Quick Query. Instead of specifying just one store, we'd
like to be able to give a qualifier. For instance, let's say we would like to see the transactions for every
store except the store we specify. Let's change the Quick Query to allow us to do just that.
Click edit query. The Save As a Quick Query dialog is presented with all the information for the current
query. You'll notice it looks almost identical to the dialog we originally filled in for the query, but it now has
a Replace old query? checkbox. If unchecked, a new Quick Query will be created based on the criteria in
this dialog. When checked, however, this will allow us to replace the original query.
For our example, let's select the Replace old query? checkbox to replace the original Quick Query with
the changes we make here.
Note: The Replace old query? checkbox takes precedence over the Save into folder directory
structure below it. If you select the Replace old query? checkbox, the query will be saved where it
currently resides, regardless of what the Save into folder directory structure indicates.
Let's change the title of the Quick Query to reflect that we may be looking at transactions from more than
one store.
And now, let's change the criterion to include a relationship in addition to the store we specify as input.
Select the checkbox under the Input? column for the Relation for criterion 1 parameter.
Quick Start Guide | How to Save a Quick Query | 44
We don't need to change the User Prompt for this, since it's fairly descriptive as is.
Click Submit to save the Quick Query. You will see the message Quick Query changed.
Now, if we go back to the Folders and Tables browser, we can see that the modified Quick Query has
replaced the original in our user folder.
Note: You may need to close the folder containing the Quick Query (by clicking
folder) and then reopening the folder (by clicking
to the left of the
to the left of the folder) to see the changes.
Double-click the Quick Query to run it. You will be presented with the new Quick Query, which prompts for
a relationship in addition to a store number.
Quick Start Guide | How to Save a Quick Query | 45
Let's use our new Quick Query to find the transactions for every store except store 1. Select does not
have the value(s) from the Choose a relationship drop-down list:
Make sure Enter store number still contains the value 1 (it should, by default). Then, click Submit.
And, voila! We now see a list of all the transactions for every store except store 1.
Quick Start Guide | How to Save a Quick Query | 46
Note: Running an existing Quick Query and then clicking Save As Quick Query from the File
menu is different from editing an existing Quick Query as described above. If we ran the Quick
Query we just created and then clicked Save As Quick Query from the File menu, we would be
presented with a Save As a Quick Query dialog similar to the following:
which is different from the dialog we saw when we saved our original query. You'll notice that
there is no criteria listed under Query Choices and there is no Replace old query? checkbox. In
essence, we have created a new Quick Query based on the results of running our original Quick
Query.
Quick Start Guide | How to Save a Quick Query | 47
Add Favorite
Since our Quick Query is so useful, let's add it to our list of favorites on the Start Page.
Go back to the Folders and Tables browser. Select the Quick Query, and then click the add favorite
action.
Now, if you look at Favorites on the Start Page, you'll see our new Quick Query listed there:
Now, all you have to do is click on your Quick Query from here to run it!
Now that you've learned how to create a Quick Query, you might want to share that Quick Query with other
users (or user groups). Check out How to Share Quick Queries and Folders on page 48 to learn how to
do just that!
Quick Start Guide | How to Share Quick Queries and Folders | 48
How to Share Quick Queries and Folders
Since you just learned how to save a Quick Query in the previous section, you may want to know how
to share that query with other users at your company. 1010data allows you to share your Quick Queries
(as well as the tables and folders that you “own”) with other users (or user groups). When you share your
Quick Query, you give permission to others to use it.
Let's use the Quick Query we created in the previous section. Find the Quick Query you'd like to share in
the Folders and Tables browser.
Note: You must be the owner of the object to grant permissions to it. The key icon ( ) directly to
the left of the query's title (circled in green in the screenshot below) indicates that you are indeed
the owner of the query.
Although we could share the Quick Query from the user folder in which it is found right now, let's add
a subfolder and move the query into it so we can explore some of the inherit permissions features that
1010data provides.
Single-click the parent folder of the query and click the Add Subfolder icon at the top of the Folders and
Tables browser.
Enter a title and a name for the subfolder. The Title can be any descriptive string for the subfolder and may
include numbers, spaces, symbols, and upper- and lowercase letters. The name (which is appended to the
Full Path in the dialog) must not contain any capital letters, spaces, or symbols other than underscores
(_), and it must begin with a letter.
Click Add. The new subfolder is added under our user folder.
Quick Start Guide | How to Share Quick Queries and Folders | 49
Now let's move the Quick Query into that folder.
Select the Quick Query by single-clicking it and then click the Move icon at the top of the Folders and
Tables browser.
1010data will ask you where you want to move the item (which will be highlighted in green). Click the new
subfolder we just created (which will become highlighted in red).
Click OK in the confirmation dialog to move the query into the subfolder. You can see the results of the
move in the Folders and Tables browser:
Quick Start Guide | How to Share Quick Queries and Folders | 50
To share the Quick Query, you must give permission for the Quick Query as well as for the folder in which
it is contained.
Note: In addition to granting users permission for the folder where the Quick Query lives, you
must also give users permission to view any of the private tables that the Quick Query uses. (In
our example, we're using a table that is public to all of the users in our group, so it will not be
necessary to do this.) You can use the view info action in the Folders and Tables browser to see
all referenced tables for a particular Quick Query. (See View Info on page 41 in this guide for more
information.)
Let's say we want to give jane_doe and john_smith permission to use our query. Let's first give them
access to the folder in which the query is contained (in our example, Store Reports) because if they can't
see the folder, they won't be able to see the query.
Go to the Folders and Tables browser and select the folder in which the Quick Query is found.
Click the edit info action for the folder. Add jane_doe and john_smith to the Users text box in a spaceseparated list.
Quick Start Guide | How to Share Quick Queries and Folders | 51
If we wanted to share this folder (and all of its contents) with all of the users who have been granted
permission for the parent folder, we would select the Inherit Users checkbox. In our example, we just want
to give jane_doe and john_smith access to our Quick Query, so we will not select that checkbox.
Note: Inherit Users takes precedence over the Users list. The user names listed in Users are
ignored when the Inherit Users checkbox is selected.
Click Save changes to save your changes.
Now let's add permissions for the Quick Query.
Select the Quick Query by single-clicking it. At the top of the Folders and Tables browser (above all the
folders), you will see the name of the Quick Query and its associated actions in parentheses after the
name. Click the edit info action.
You will be presented with a dialog to edit all of its information. The areas we are interested in, with respect
to sharing, are Users and Inherit Users.
Quick Start Guide | How to Share Quick Queries and Folders | 52
In the Users text box, you can explicitly list all the users who can run this particular Quick Query. By
default, Users contains only the name of the user who created it. You can add other user names to this
text box in a space-separated list.
However, we can instead use the inherit permissions features that 1010data provides. Since we already
gave jane_doe and john_smith permission for the parent folder, all we have to do is select the Inherit
Users checkbox and they will be able to run this Quick Query.
Note: Inherit Users takes precedence over the Users list. The user names listed in Users are
ignored when the Inherit Users checkbox is selected.
Although it's not necessary for sharing Quick Queries, you may want to change the name of the query
to something that is a little more intuitive. By default, the system generates the name when the query is
created, incorporating a long numeric string with the owner's user name appended to it.
Quick Start Guide | How to Share Quick Queries and Folders | 53
For our example, let's change this to something that is a little easier to read.
Note: If you change the name of the table from the default system-generated name, it must not
contain any capital letters, spaces, or symbols other than underscores (_), and it must begin with a
letter.
Let's change it to trans_by_stores.
Now, click the Save changes button at the bottom of the dialog for the changes to take effect.
Now jane_doe and john_smith can run our Transactions by Store(s) Quick Query!
Note: After a Quick Query's or folder's permissions are changed, any impacted users must log out
and log back in before the new permissions will work.