Data Discovery and GovernanceBenefits, Challenges, Guidelines

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Why Govern Your Self-Service BI, Analytics, and Data Discovery Environments?

Data governance helps organizations realize the benefits of self-service analytics and data discovery, and avoid issues such as disparate and disconnected tools and multiple versions of the truth. Find out some more reasons why here….

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Reason #1: Privacy and Security

As more users gain access to enterprise data, the need to protect it from unauthorized viewing increases exponentially.

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Reason #2: Confidence in Safe Sharing of Analytical Content

A governed environment ensures that colleagues, customers, business partners, and other stakeholders are comfortable sharing the insights they have, such as

• Interactive visualizations• Reports and charts• In-document analytics• And more

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Reason #3: Having Confidence in Your Data

Surveys show that as many as 60 percent of companies consider their data to be unreliable, with as much as 25 percent of the information in the average database containing inaccuracies.1

1 “The Impact of Bad Data on Demand Generation,” Sirius Decisions, 2013

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Reason #4: Fraud Prevention

Offering tools to a broader user base creates the risk of inappropriate or even illegal use of enterprise information.

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Pitfalls of Poor Governance

According to Eckerson Group, power users in an ungoverned BI environment “operate in silos – independent of other users and analysts – and create spreadmarts that conflict with other corporate and departmental reports.” 2

Read on for some of those pitfalls…

2 Eckerson, Wayne. “Governed Data Discovery: Balancing Flexibility and Standards,” The New BI Leader, March 2016

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

Pitfall #1: Data Silos

Data Silos hinder the sharing of analytics content across departments and business units.

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

How can I avoid creating Data Silos? Read more here: http://bit.ly/BigDataIssues

Pitfall #2: Dirty Data

Research from Experian Data Quality shows that inaccurate data has a direct impact on the bottom line of 88 percent of companies, with the average company losing 12 percent of its revenue.3

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

3 Davis, Ben. “The Cost of Bad Data: Stats,” Econsultancy, March 2014

Achieving Governance in Self-Service Analytics and Data

A good governance plan must be backed by the right supporting technologies. Bad data drains resources, leads to poor decision-making, and impacts the bottom line. With Information Builders, organizations can create and deploy robust self-service analytics and data discovery environments, while protecting the availability, reliability, security, and quality of the data being delivered through those environments.

4. Confidence in Data

9. Achieving Governance

6. Pitfalls5. Fraud Prevention

7. Data Silos 8. Dirty Data

3. Confidence in Safe Sharing

2. Privacy and Security1. Why?

For more information, visit us at informationbuilders.com and download our full white paper at: http://bit.ly/2hakhUi