Enterprises must prioritise security, governance and user adoption for successful implementation
The urgency of implementing enterprise data management strategies comes from an acute awareness that businesses need to put their data to work effectively to influence decisions and efficiency, and ultimately help steer the direction of the business.
An enterprise data strategy being driven separate from the C-suite, which is designing the business strategy, is a recipe for an unsustainable disconnect. The executives, being the drivers, will enable budgets to access new technologies, and – crucially – initiate effective change management.
ITechnology Series Guest Post: Mind the Gap: Raising Threat Defenses in the Hybrid Workplace
Obstacles to adoption of enterprise data strategies
Budgetary, infrastructure and skill constraints are global phenomena, and Africa is no different. Across regions, the further one ventures from major centres, the less reliable – or available – connectivity becomes. But, there are reasons to be optimistic: Starlink, for example, being available in Nigeria and Mozambique, will no doubt enable far more adoption among enterprises to leverage data more effectively.
Corporate South Africa, despite energy challenges, has been more fortunate in that infrastructure has been more advanced and stable for a longer period of time. This has accelerated the widespread acceptance by enterprises that they have to invest in data strategies to remain competitive and make accurate decisions.
Data literacy is also improving exponentially. Today we get requests from countries north of South Africa for assistance in regression analysis and correlation coefficients.
ITechnology Series Guest Post: Unlocking the Power of an Intelligent Enterprise
Here are some of the crucial components of an enterprise data strategy:
Security
Security is multidimensional and data integrity is a crucial component. An organisation that has poor data quality is going to make incorrect assumptions, which is a business and security risk.
End users are another important cog. Ensure the right people have the appropriate level of access to the right data. Beyond this, user education is paramount.
Governance
Good data governance should enable users to leverage their data in the most efficient way possible, while still ensuring integrity, security and appropriate accessibility. There needs to be a healthy balance between access control and ease of access and use.
User adoption
The key is effectiveness and ease of use. An enterprise needs a platform that is as intuitive and uncomplicated as possible. There is little use in one department pulling data from a spreadsheet, and another using some or other BI interface. The data champions identified in the change management have an easier time helping colleagues when using a unified, intuitive platform.
Different levels of the organisation need different levels of insights. An executive may want a bird’s eye view, while another may request the “why” to drive important decisions. Platforms like Qlik further enable users to dig deeper and then easily drag and drop charts to explain and narrate a story about the business. The same principle holds true when leveraging the predictive power of Qlik – extracting insights for the business must be intuitive and simple.
ITechnology Series Guest Post: Data Mastering as a Key Component of Data Mesh