When you sign up for eazyBI then new trial account will be created for you.
One eazyBI account contains a set of data which can be analyzed by one or many account users. In any given time, you can work with one selected current account (you will see the current account on top right header menu). You can select current account either from Home tab or from account selection drop-down in the top right header menu.
After the end of the 30-day trial, you will need to select account plan. You can select either private plan (only account users can access account data) with monthly subscription or you can select public plan if account contains public data and any anonymous user can access it.
User who creates eazyBI account is Owner of the account. Owner has all rights for this account and also can add additional users to account. In case of private accounts only specified account users will have access to account data.
Read more about adding additional account users to your account.
After creating new account you need to import data which you want to analyze. There are two ways how to import data - either upload source data files or import data from source application for which eazyBI data import is defined.
Currently import from Excel and CSV format files are supported (other formats will be supported later, please write feedback if you want support of some specific format). After upload of source data file you need to define mapping from source file columns to cube dimensions and measures (see Cubes, Dimensions and Measures below).
Import from source applications provides faster way for data import and start of data analysis. For each source application data will be uploaded into predefined cube structure and default analysis reports will be created. After initial upload regular new data import will be scheduled automatically (for paid subscription plans).
See available source applications that eazyBI is integrated with.
Imported data are stored in multi-dimensional data cubes. Cubes contain fact data that are divided by dimensions and each detailed fact “cell” contains measure values about that fact.
This is example of Sales cube that has Customers, Products and Time dimensions and has measures Sales amount and Units sold. Each detailed cube “cell” contains sales amount and units sold for particular product, customer and time period:
It is easy to illustrate cube with three dimensions but you can have as many dimensions and as many measures as you need in one data cube.
All measures in the same cube share the same dimensions. If in one account you want to store different types of measures that do not share the same dimensions then you can create several different cubes.
Typical cube dimensions are Time, Customers, Products, Locations, Employees, Projects etc. Use dimensions that are best suited to your business domain.
Each dimension can have either just detailed level of all dimension members or you can define hierarchy with several levels. For example, Customers dimension could have Country, State and Customer Name levels.
All measures are automatically aggregated (typically as sum of detailed level values) in upper hierarchy levels. E.g. looking at Sales amountmeasure at Country level will give total sales amount for this country.
Typically each dimension has All level with one All member which aggregates all dimension members.
When you upload source file with date (or date & time) column then automatically time hierarchy will be constructed for corresponding dimension. Time hierarchy will have Year, Quarter, Month and Day levels which can be used to get totals of measures at selected time period level.
Any item in a dimension is a member of that dimension.Each dimension also has a default member, called All Members, that includes all dimension members (its children).
For example, in a Country dimension, each country is a member and each continent (group of some countries) is a member, and All Countries (group of all dimension members) is a member of Country dimension.
Measures typically are integer or decimal values that can be accessed either at detailed dimension member level or can be aggregated at higher dimension levels. Typical measure examples could be Sales amount, Units sold, Cost amount, Transactions count etc.
Dimension members have properties. The role of a property is to hold information about a particular member. Property could be anything that describes member details. For example, a User dimension member can be a person (user) and the property of each user can be an address (string), age (number), date of birth (date). In reports, properties are displayed only at a particular user level.
Sometimes you want to calculate new measures from other existing cube measures - these are called calculated measures. For example, you could define Profit calculated measure as Sales amount measure minus Cost amount measure. And then you could also define Margin % calculated measure as Profit measure divided by Sales amount measure (and display result as percentage).
You can also define calculated members in other dimensions. For example, you could define in Customers dimension new calculated memberNorth America as sum of USA and Canada members. Calculated member is also a member of dimension.
Calculated member formulas are defined using MDX language. Basic arithmetic formulas can be created very easily but by learning other MDX functions you will be able to create any calculated members you need. Read more about creating calculated members.
MDX is a Multi-Dimensional eXpressions query language that allows you to query data cube and add business logic to the cubes. You can define new calculated members, sets, or get member properties using MDX.
Analyze data and create reports
After importing data from source files or source applications you can go to Analyze tab and start to explore data in created cube. You can start creating table reports by dragging needed dimensions to columns, rows and pages and exploring your data at different dimension levels. After selecting needed data in table report you can switch to different chart reports to explore your data in more visual way.
When you have created report layout that you want to use frequently you can save this report with given name. When later you will open saved report then you will get latest results from data cube using saved report layout.