Foundations of a Data Centric Organization A NDREW K A R CHER SQL SAT U R D AY #740 A P R IL 1 4,

Transcription

1 Foundations of a Data Centric Organization A NDREW K A R CHER SQL SAT U R D AY #740 A P R IL 1 4,

2 About Me LinkedIn, Twitter Company Senior Data Architect at BD Organizer for SQL Saturday OC, President San Diego.Net User Group, Organizer Data Engineering San Diego Disclaimer: All opinions expressed in this presentation reflect my personal views and not necessarily the opinions on my employer.

3 Why are YOU here?

4 Agenda Discuss the problems in a non Data Centric Organization What are some of the attributes of a Data Centric Organization What can you do to start moving your organization to be more data centric

5 The topic of being Data Centric is like a

6 How software projects start

7 6 Months Later

8 So how does this make you feel

9 Application Centric Organizations Process Flow A Business Problem or a new need is identified within the organization. An executive is sponsoring a project to find a solution The executive gets a report from Gartner, goes to a conference, talks to his buddies and gets some phone calls from some salespeople. The executive talks to IT. IT says that their backlog is full. Executive hires a consulting company to implement purchased product that will change the world. A week before the project goes live you are called and asked to help integrate the data with some existing data so the executive can get reports on how the new software is doing

10 The problems is only getting worse 10 years ago you needed Now all you need is a credit card

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14 So, What is Data Centric

15 Data is an Organizational Asset Data is often not recognized because it does not show up as an asset on the balance But, if data is not an organizational asset, then why are there companies whose whole value is because of the data they have? Google, Facebook, Amazon, Netflix Everyone from the CEO down needs to recognize that Data is an asset It has value Deprecates over time Needs to be Protected Needs to be consistently invested in Data is not different than Marketing, Finance, HR, Engineering, etc.

16 Track and Store Everything Peter Drucker If you can t measure it, you can t improve it If you are making a decision, you have to back it up with data. No decision or change can be made without first asking the question What is the data behind the decision? What new data or changed data will occur with this change What data are you using to decide if this is the right decision The one thing that you never want to hear in a data centric organization is We don t have any data for that

17 Data Quality is a Priority Capturing data is only the first step If the data is not high quality, how can you possibly use it to make decisions? Think about your accounting books If your books are not in order or correct, how can you get a loan, file taxes, get investors, etc. If you truly want to be data centric how can you make decisions on data if you do not know if the data is correct?

18 Access to Data is Uniform across the Org This does not mean that data necessarily has to be in a single system (although it helps) But it does need to be accessible to everyone (With appropriate security controls, obviously.) If you are trying to see the profile of the user, you need to have access to a full view of the user You cannot properly make a decision if you do not have access to all the data.

19 Data is part of Every Project/Feature Every Project has representation with Data Owners Any new data that is generated cannot be created without a plan to map that data to the enterprise. Every result of every project or feature is evaluated based on the data that is generated on whether that project or feature is successful No project or feature is started without the backing of data that it is needed.

20 The Path to Data Centric

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22 Hierarchy of Data Needs Answer Ask Derive/Curate Make Available Capture Data Scientists, AI, Machine Learning Data Analysts, Vizualization Engineers Data Engineers Integration Engineers Data Platform Engineers

23 It Starts at the Top Data Centric is a mindset that needs to be driven from the top There is no Easy button for a transition to being data-centric Moving to Data Centric requires buy-in for everyone in the organization. If it is not a priority at the top it cannot filter down to everyone else.

24 Spreading the Word is Everyone s Responsibility Everyone needs to be focused on promoting the vision, benefits, and details of being data centric. People need to have guidelines and principles for how to be data centric. Everyone in the data organization needs to be a promoter of being data centric.

25 Governence\Decision Making All data related activities and decisions need to be transparent Data Governance does not need to mean hard to change. Utilize a decision matrix like RACI to better understand decisions and who needs to make them

26 Measure Progress Need to eat our own dogfood and measure our progress. How much Data is Captured? How many people are using it? Collect data on data usage, successes, failures, etc. Present data to rest of the organization

27 Everyone is a Data Owner Every single person is an owner of data Whether they are producing, storing, using, or reporting or data. Everyone should have the opportunity to use data to improve the business

28 One Subject, One Source Organizations need to have a singular view of key data points or who owns the definition Additional versions can derive additional numbers, but they need to reconcile back Need to avoid having competing numbers for the same thing Have a decision making process for defining ownership and development of key metrics

29 Conclusions

30 P3T People, Process, Policy, Technology People are the key to success. Everything centers on the actions of people. People need to follow Processes. If people are failing, often times they are not sure of policies or what they should be doing or why Policies sometime need to be the arbiters for people. It also help guide people on what they should do and why Technology is an enabler, but is never the sole solution. Technology needs to ensure it is not preventer of solutions

31 Data Solutions need to solve Business Problems Before starting data projects always focus not on the technology, but what business problem the data is going to answer or solve. You want to know Business Problem you are trying to solve What is the data that indicates this is a problem What data do you think you need to answer the question How will the data be used to answer the question Once you have the answer what is the action to be taken from the answer

32 Questions? A K A R AKARCHER