Chris Josefy Killing Traditional Data Management Session #2969

Transcription

1 Chris Josefy Killing Traditional Data Management Session #2969

2 LEARNING POINTS Stealth data governance can create effective data stewards without them actually knowing what they are really doing Adopt a "just do it" philosophy to data governance by utilizing Information Steward and starting without any formalized processes or structures Break out of the academic definitions of data quality and instead think of data quality in terms the business understands to create scorecards they will adopt with little or no training

3 PURPOSE: WHAT WE DO At EP Energy, we have a passion for finding and producing the oil and natural gas that enriches people's lives

4 EP ENERGY TODAY ALTAMONT HAYNESVILLE WOLFCAMP EAGLE FORD

5 WHY DO WE WANT DATA GOVERNANCE? Everyone wants good data Right data, right place, right time, right person, right decision, right? It s not the why that is the problem, it s the how

6 TRADITIONAL MODEL Highly Formalized Committees, Councils, PMO SMEs, Data Stewards, Facilitators, Chairs Policies, definitions Feels large because it is large Often hard to gain buy in and support Requires new roles, responsibilities, and people to be in place Source: MITRE Information and Data Management

7 NON-INVASIVE DATA GOVERNANCE Non-Invasive Data Governance is a Trademark of Robert S. Seiner Same concept, but with a few key differences Start with practical, high value use cases Don t create a position, don t create titles, but rather identify those already doing the work and add accountability and expectations Still utilizes councils, formalized roles, etc.

8 STEALTH DATA GOVERNANCE Don t Don t call anyone a data steward Don t form a council Don t ask for executive sponsorship Don t tell people what you are doing (to an extent) Results Do Increase data quality quickly without overhead Use a task force approach Use your existing relationships with people already maintaining data Use tools you already have at your disposal Stealth Data Governance is not really trademarked, but it would be cool if it was

9 HOW DO YOU START? Just do it Don t wait for a larger initiative or an executive/leader on a mission Don t wait for data quality problems to pop up and make this is an urgent effort Find a motivated person in IT with a passion for increasing data quality Find a test use case where solving a specific data challenge would provide value to the business Call together a task force of business and IT to talk about improvements that could be made Use Information Steward to get the users to intuitively and enthusiastically improve data quality Repeat

10 INFORMATION STEWARD The tools to enable Stealth Data Governance may already be inside your organization If you aren t using Information Steward today, call someone at your office right now and get started Information Steward is one of the most practically useful toolsets in BusinessObjects, one of the least used, but also one of the most unique

11 THE EP ENERGY CHALLENGE To measure our execution success, we must accurately capture: Daily drilling and completion costs against plan Cycle times throughout the drilling and completion process against plan Single software program used to track entire drilling and completions program Data captured by users of various backgrounds, skill levels, and training Daily estimated costs entered at the drilling rigs (80+ laptops deployed to the rig sites) Cycle times captured by technicians in corporate office

12 THE EP ENERGY SOLUTION Fully automate all business rules into Information Steward Formalize rules already accepted by the business Structure the scorecard to be business relevant and intuitive Hand it back to the business to help them better manage the work they already do Create custom universe on top of data insight database to allow structured reporting Ability to structure reports for management Automated subscriptions each week with detailed lookback data

13 TRADITIONAL DATA QUALITY DIMENSIONS Accuracy - Determines the extent to which data objects correctly represent the realworld values for which they were designed. Completeness - Determines the extent to which data is not missing. Conformity - Determines the extent to which data conforms to a specified format. Consistency - Determines the extent to which distinct data instances provide nonconflicting information about the same underlying data object. Integrity - Determines the extent to which data is not missing important relationship linkages Timeliness - Determines the extent to which data is sufficiently up-to-date for the task at hand. Uniqueness - Determines the extent to which the data for a set of columns is not repeated Source: SAP

14 TRADITIONAL SCORECARD What makes more sense?

15 BUSINESS RELEVANT SCORECARD What makes more sense?

16 SCORECARD STRUCTURE Key decision to structure data domains and utilize custom quality dimensions to organize data so that it would natively connect with the way the users view the world Data domains broken into business areas Quality dimensions created to show functional areas Completions Construction Drilling Production By structuring the data this way, the uptake of the tool was significantly enhanced by making it incredibly easy to digest

17 CUSTOM UNIVERSE Business users wanted to receive summary reports on Friday Created custom universe on top of data insight database in order to provide detailed information on rules and score Created schedule to send report on Friday, and also includes link to interactive scorecard

18 RESULTS More and more users are taking ownership of data quality Data quality scorecard is being reviewed out on the drilling rigs in real time Technicians make daily upkeep of the data a priority Current schedule computes scorecard daily; team would like to compute multiple times during the day to more actively monitor quality Business is fully engaged and bought in Explosion of requests for additional rules and validations to improve other parts of our drilling and completion process Multiple disciplines and systems now actively working on data quality scorecards

19 MASTERING DATA ACROSS SYSTEMS

20 BEST PRACTICES Identify individuals already maintaining data in their day to day jobs and enable them with better technology Utilize your existing investments and unlock the power of Information Steward Create scorecards broken up into logical units based on who the audience is (business area, application) Utilize customization capability to create data dimensions that makes sense to your users

21 KEY LEARNINGS Stealth data governance can unlock the benefits of data governance without the overhead and formality of a traditional model Motivated individuals can utilize Information Steward to start their own Stealth Data Governance initiatives to make a difference today Don t be afraid to utilize the tool to it s fullest in order to design rules and scorecards that your business will immediately adopt

22 QUESTIONS Q&A Chris Josefy

23 STAY INFORMED Follow the ASUGNews team: Tom Chris Craig

24 SESSION CODE 2969