Integrating the Dataverse

  Whenever you are triaging a problem, you have to focus on what is in front of you, but you cannot forget about how your actions will impact your overall desired outcome.   For example, let’s imagine you are managing a thriving new software company.   Your software has gone viral, and you have to grow ASAP to handle support and new development.   What is your knee-jerk reaction?   Get as many bodies as you can.   You bring in a wave of contractors, from project managers to developers.   Your short-term needs are met, but in 3 months, what happens?   You grew too fast, and customer complaints are starting to expose the weakness of not having a fully functional organization.   A data governance practice usually has the same problem.   There is always one pillar that needs more immediate attention at the beginning: data quality.   Even if that is the case, you cannot pour all of your gas on that fire; you still have to plan for the ...

  As we continue to remove the mystery around data strategies, we will spend the next few weeks diving into the components and principles that make up data strategies.  My hope is that as you start putting the pieces of this puzzle together in your own mind, you will start to see that with a methodical and measured approach, a solid data strategy is within your grasp.  Today, we are going to start focusing on data governance.   Data governance is a key component of a successful data strategy. It ensures data reliability, security, and usability throughout an organization. Data governance manages data from creation to deletion. It involves defining roles, responsibilities, processes, policies, and standards that guide data management and protection. But don’t worry.   We are going to take our time.   Today, we will cover data governance at a high level, and as the days go by, we will get into the details.   When we are done, you will all have greate...

We are progressing in our data governance by building out the framework.  We are moving data into areas that the business can use it but how do we know they should use it?  More importantly how do they know that they CAN use it? So much of what we do relies on trust.  The business trust that we will understand what they need so that we can deliver reliable data.  The first time they find an issue that trust is broken.  Part of our framework builds out data validation processes but how do we put that into practice? One of the first things we will need to do is check ourselves. Y our data governance framework can be used to create natural data quality checkpoints. Is your data pipeline ready to migrate? Did you check it? When your process captured the requirements did you ask who in the business would validate the work? Your processes are the first place to start checking your data. Some specific examples of how you can use your data governance framework to cr...

The next step in our data governance journey will be setting up the data governance framework. In some ways this is just like the frame that your home is built around. In a home the frame lays out the exterior and interior walls, provides a place for electrical and network wiring, a place for insulation, and more importantly exterior and interior wall coverings like brick and sheetrock. The data governance framework works in the same way. By using principles and guidelines it provides structure around your data so that you can implement things like data cleansing rules, roles around data, and the tools that you allow the business to use. The end goal is to make sure that your data is being used in a consistent and compliant way so that everyone using it gets the same answers. You can see why this is a task that is easier said than done. Your data governance framework should include the following components: Data governance roles and responsibilities : This section should de...

Data governance is a subject that most people would rather let someone else cover.  It is hard to do, hard to maintain, and hard to communicate with the business.  The business just expects the data to be right, it does not want to know what goes on behind the curtains.  Today we pull back the curtains to expose some of the things you will need to consider when you make it to this stop on your data strategy roadmap. First lest define what data governance is.  In a nutshell data governance is a set of business rules and processes that are supplemented with technology to achieve standardized data that can be checked and verified.  A key part of data governance is that the results can be repeated and can be validated by external sources if need be.  Data governance is a tool that can be used when you are in a heavily audited industry like banking to show the path that your data has taken and the reasons for the changes.  It will also naturally lead you do...

We have spent the last month going into significant detail showing you why you need a data strategy and how to document your strategy with a roadmap.  For the next few weeks we will start using that roadmap to move your organization towards your business objectives. Our first stop will be your data governance plan.  Why is this the first place to stop?  To be honest it may not be.  There is a lot of overlap with future steps including picking the correct software, team members, and third party vendors that to help you implement the entire strategy so it does make sense to have the data governance process underway as early as possible.  The truth may not be that practical though.  Not every organization is ready to push through a true data governance plan.  And yes this will be a push.  No organization likes it when someone tells them they are doing something wrong especially if that someone is a teammate.  That is what data governance does so...