Delivering Business Analytics: Practical Guidelines for Best Practice

Chapter 10

Information Management

Organizations spend an absurd amount of time trying to manage their data. Big data only exacerbates this problem; to take advantage of an asset, it needs to be fit for purpose.

This is especially true in business analytics. The time a typical team spends managing data usually dwarfs the time it spends actually creating insight. Despite this, few teams have a plan when it comes to their data. Rather than see data management as a key activity, they usually see it as a small part of a bigger process. Through a blend of heroic effort and sheer will, teams limp along constantly wondering why their lives are so hard.

This is backwards. Data management is the big, bad, and ugly part of business analytics. A team without a plan is a team doomed to inefficiency. Most organizations struggle with:

• Designing their information assets to maximize reuse
• Minimizing the time they spend managing data
• Designing flexible processes that can be used across many situations
• Deciding what data they capture and process

The solutions described here focus on frameworks and techniques that help describe and overcome these challenges.

CREATING THE DATA ARCHITECTURE

CASE STUDY: WHY READ THIS?

When will this help?

Read this if your data is a mess and you don’t know what to do about it.

How will it help you?

Using this approach will help you structure your data to encourage reuse.

What are the guiding principles?

• Understand your data
• It’s better to have too much data than ...