1. Building a Project

1.1. The process of building a project consists of the following:

  • Creating a project name

  • Bring data into the system

  • Forming relationships between data

  • Developing Data Exploration Tools (widgets)

  • Expanding Analytics with Natural Language Processing and or Machine Learning

1.2. Creating the project and bring data into the system.

The first step in building a project is creating that project in the system. This is accomplished by creating a project name and associating the primary data table with the project. This primary data table can be a c.s.v. file, a table from a database, or files associated with the file/web crawler.

1.3. Understanding Data Types

Not all data is represented in the same manner even though it may look the same on the screen. Numbers may be floats (decimal points) or integers. Time series may look like text. All c.s.v. imports will be represented as text values. This becomes an issue when developing relationships between data tables and how data interacts with widgets - text acts differently than numbers.

The tools in the data importer allow the user to recast data to different types provided the format of the data is compatible with the new type. A float can’t be converted to an integer but an integer can be converted to a float. Text can be converted to numeric values. If the text contains a decimal point, it’s a float.

1.4. Establishing Relationships in Data

Different data tables on a topic can be linked by a common data field in the data table. For instance a state name, a customer i.d., or a word (advanced feature). This is handled as either a primary-foreign key relationship or a many-to-many relationship in the application.

1.5. Mapping Latitude and Longitude

The tables section is where the user configures geographic points for the mapping widget. Points are the representation of latitude and longitude on the map. Points can be configured topic::represent relative areas such as 500 meters, 5000 meters, etc.