Concepts

What is Data Manager?

The Data Manager is a solution embedded into LityxIQ. It includes a very powerful set of functionality used to import, clean, manage, and manipulate data. Once you create data with the Data Manager, it becomes available consistently in all other areas of LityxIQ, including Insight, Predict, and Optimize.

Derived Datasets

A Derived Dataset in LityxIQ is a dataset created from one or more other datasets. It is defined by specifying up to seven steps which are processed in sequence. Each step is optional except the first. - Select an incoming dataset or datasets. These will be the source data that is goes through further processing steps. Multiple datasets can be selected, in which case they are stacked on top of each other (analogous a UNIION query operation as would be familiar to SQL users) to start the data...

LityxIQ Datasets

In LityxIQ, data is stored in what is referred to as Datasets. Just like most analytic applications, LityxIQ stores data in its own special format which is fully maintained on the backend. In the case of LityxIQ, this format is a high speed data structure that supports big data and fast parallel operations. As in other applications, a LityxIQ dataset can be thought of as a table with rows and columns, where rows generally represent different observations (e.g., customers, transactions, products)...

Viewing Available Datasets

The ‘View Datasets’ link within DATA MANAGER provides a list of all available datasets within a selected library. It is here that you can create new datasets and manipulate existing ones. After clicking the ‘View Datasets’ link, the working area in the right pane of LityxIQ will look like the following. Important areas are explained in more detail below. - Dataset Library - This drop down box displays a list of all of the dataset libraries to which you have access. Select the library...

Variable Names

LityxIQ provides a good amount of flexibility in naming variables in datasets. This is very beneficial for the sake of easily understanding what is represented in the data because you can give variables descriptive names. However, there are still some restrictions on how variable names are created, as described below. Important Note: Variable names are case sensitive. This means that the names ABC and Abc (for example) are considered different variables. This is important in particular when ref...

Data Types

Every variable in a Lityx dataset can hold data of a single data type. The dataset's dictionary is where formats are determined and available for viewing. The data types supported by LityxIQ are described below. Data Types for Holding Numbers Integer - integer data types hold data in the form of whole numbers. There are four sub-types (also called Formats in LityxIQ) that are differentiated based on the range of possible integer values that can be stored. From a technical perspective, this ...

NULL Values

The NULL (or written Null or null) value in LityxIQ can be thought of as an unknown or missing data value. It is analogous to NULL values you may be familiar with in SQL tables, or NA values in other applications. Any data value for any variable in a dataset can have the value NULL. Importing NULL Values from a Raw Data Source For Raw datasets, NULL values will be imported from the raw data source if they exist there. For example a delimited text file may contain NULL values as indicated...