January 16th, 2020
You know your data is one of the (if not, the) most valuable company asset, therefore priority should be placed on the quality and governance of that data….and the ability to quickly and easily provide data to analysts for business intelligence – that’s the real value! However, companies still struggle with data sprawl and data silos and the data management myths they create.
According to a recent augmented data management study by NVP only half of the firms surveyed are managing data as a business asset. We find that many companies are still questioning the investment into a data management solution and most of them are buying into one or more of these myths.
Reality: There’s no need to solve all of your data silo problems at once. Start your data management project with one use case, then expand to others. We suggest starting off a “low hanging fruit” project so you can quickly test the solution and realize results.
For example, start with creating a unified view of all your customer data for better marketing analytics. Each project afterward will be increasingly easier and faster to deploy as your data is connected and cataloged from multiple sources and locations.
Reality: Any company that needs to share its enterprise data across departments or systems can benefit from data management. Using customer data as an example, even small companies probably have a CRM used by sales and marketing, data from the finance department and data collected by training, support and service teams. Imagine what you can do with the insights gained through a holistic view of each customer’s experiential and transactional history with your company.
Reality: This might be the biggest myth of them all. The purpose behind data management is to make life easier for both IT and business. The right data management solution increases IT agility and accelerates time-to-business-value.
IT can eliminate bottlenecks and reduce their workload by providing self-service, governed access to data directly to those who need it. Workflows can be automated and concerns about data privacy and regulatory compliance can be quelled with pre-permissioned, role based-access and data lineage, masking, and tokenization.
Reality: A good data management solution does not require any “lifting and shifting.” Although there are many advantages to moving your data to the cloud, your goal should be to unify your data for a single view into every data asset, no matter where it’s located – on-premises and in the cloud. Think of it as a “virtual data lake.”
Reality: The build vs. buy debate has been around forever and the answer is always “it depends.” The major consideration comes down to cost. Can you afford the time and resources dedicated to building a custom solution in-house? You also want to consider long term costs. Can you dedicate resources to continual upgrades and maintenance?
You must also factor in opportunity costs. What else could your staff be working on? And, how much time can you afford to spend on this initiative? We helped Nuveen, a subsidiary of TIAA, integrate 3rd party ESG data to create an award-winning responsible investment platform in only 6 months! Can your team create and deploy a solution in 6 months? At what cost?
Reality: The best data management solutions are flexible and vendor-agnostic. Love your ingestion tool? Keep it. Do your data analysts prefer multiple BI tools? No problem.
Achieving true data management is about having one holistic view of every single data asset in your ecosystem for the purposes of accelerating and improving business intelligence and controlling governance for regulatory compliance. Find a solution that works with the systems and tools you currently love and it will only make your life easier.
According to the NVP survey, about three-quarters of respondents say that business adoption of big data and AI is a challenge. Over 90% report that the challenges to becoming data-driven are in people, processes, and culture—not technology. But we know many of these challenges to be data management myths that are quite easy to overcome… if you have the right data management technology.