Understanding Your Organization's Data Assets - discovery - 23.1

Spectrum Discovery Guide

Product type
Software
Portfolio
Verify
Product family
Spectrum
Product
Spectrum > Discovery
Version
23.1
Language
English
Product name
Spectrum Discovery
Title
Spectrum Discovery Guide
First publish date
2007
Last updated
2024-02-07
Published on
2024-02-07T17:21:58.768552

If your organization is like most, you have a large number of data assets containing everything from customer contact information and purchase history, to financial data, to transaction records, and more. These systems can run on different platforms, sometimes managed by different departments with different security controls. There is potentially a wealth of data available to you to answer business questions, but it is a challenge to figure out which systems contain the data you need, which systems to trust, and how they're all connected.

Spectrum Discovery provides the visibility you need to identify the most trusted sources of data to use to satisfy a business request.

  1. Start by connecting the physical data assets in your organization to Spectrum Technology Platform. See Connections.
  2. Then, define a physical data model to represent your data assets in Spectrum Discovery. Going through this process will help you understand how your data assets are structured, such as the tables and columns in each database, and the relationships between tables. See Adding a Physical Data Model.
  3. With an understanding of the physical data assets available to you, you will want to make sure that the underlying data is of good quality. Use profiling to scan your data assets, identify the types of data contained in them (such as names, email addresses, and currency), and identify incomplete and malformed data. See Creating a Profile.
    Tip: Using the reports from profiling, you can create Spectrum Technology Platform flows to improve data quality. If you have not licensed one of the data quality modules for Spectrum Technology Platform, contact your Precisely Account Executive.
  4. With a physical data model created and a clear understanding of the state of your data through profiling, you can create logical models to represent the business entities that your business wants to understand, such as customers, vendors, or products. In this process you select the sources for the data you want to use to populate each entity, such as customer addresses and purchase history. See Creating a New Logical Model.
  5. To maintain your data assets you need to understand how they're all connected and how data flows from source to destination. Use the Data Flow Analysis feature of Spectrum Discovery to view the dependencies between data sources, destinations, and the processes that use the data. With this information, you can make informed decisions about the impact of a change to data sources, troubleshoot unexpected results, and understand how Spectrum Technology Platform entities like flows, subflows, and Spectrum databases affect each other. For more information, see Viewing Data Flow Analysis.