Five Ways to Solve Data Centralisation Challenges
Dr Emmanuel Ogungbemi
I help you break into data science and AI with practical tips, real-world insights, and the latest trends.
In our rapidly digitalising world, businesses and organisations produce and consume vast swathes of data daily. Centralising this data — consolidating it into unified repositories or systems — seems like the obvious way to harness its potential.
However, the journey to centralisation is fraught with obstacles. From maintaining data integrity to navigating security pitfalls to ensuring various systems can 'speak' to one another, these challenges can overshadow the potential advantages of centralisation, which includes streamlined operations and informed decision-making.
Given these complexities, how can an organisation ensure successful data centralisation, maximising benefits and minimising pitfalls?
1.?????? Establish Clear Data Governance - Defining the Rules of Engagement
Governance is at the heart of data centralisation. Therefore, setting clear policies and standards around data collection, storage, and usage is vital. The administration involves determining who has access to what data, maintaining data quality, and resolving discrepancies. By delineating responsibilities and accountability structures, organisations can ensure that their centralised data remains accurate, consistent, and trustworthy.
IBM suggested that you build a data governance program by following the following process.
i.???????????????????Defining your data strategy and data governance goals and objectives
ii.??????????????????Securing executive support and essential stakeholders
iii.???????????????? Assess, build and refine your data governance program
iv.???????????????? Document your organisation's data policies
v.??????????????????Establish roles and responsibilities
vi.???????????????? Develop and refine data processes
vii.??????????????? Implement, evaluate, and adapt your strategy
?2.?????? Implement Robust Data Integration Tools - The Glue that Binds Data Together
According to Gartner, data integration comprises the architectural patterns, methodologies and tools that allow organisations to achieve consistent data access and delivery across a broad spectrum of data sources and types to meet business applications' and end users' data consumption requirements. Different departments within an organisation often operate in silos, each using its tools and software. Data integration tools act as a bridge, linking these disparate systems and facilitating seamless data flow. With the right tools, redundancy is minimised, efficiency is increased, and the foundation for a single source of truth is laid.
?3.?????? Prioritise Data Security - Guarding the Digital Treasure Trove
As data is centralised, its value – and the allure for malicious actors – grows. It becomes imperative to bolster defences against potential breaches. Investing in encryption, setting stringent access controls, and conducting regular security audits can help against breaches. In addition, organisations can protect data from internal and external threats by treating it as a valuable asset.
Prioritise data privacy for the following reasons.
i.???????????????????Data breaches will harm your business
ii.??????????????????Data privacy is essential for your brand reputation and value
iii.???????????????? Data Privacy will help build customer trust and loyalty
iv.???????????????? Data privacy will deliver a competitive advantage
v.??????????????????Data privacy can drive Innovation through data optimisation
4.?????? Foster Interdepartmental Collaboration - Breaking Down the Walls
While technology can centralise data, it's the people who need to use it. Collaboration between departments ensures that centralised data is utilised to its fullest potential. Regular workshops, training sessions, and cross-departmental projects can help inculcate a culture of data sharing and collective decision-making.
Forbes suggested that these platforms can help ensure everyone is on the same page and working toward the same objectives. It can be helpful when different departments work together on a project, as it can help ensure everyone knows what needs to be done and when.
5.?????? Continuous Monitoring and Quality Checks - Keeping the Data Engine Tuned
Just like a car requires regular maintenance, centralised data platforms need ongoing monitoring. Automated tools can flag anomalies or inconsistencies, while periodic manual reviews ensure the platform meets organisational standards. This two-pronged approach ensures that the data remains accurate, relevant, and actionable.
These are five tips for monitoring to ensure data quality.
i.???????????????????Use of automated monitoring and alerting tools
ii.??????????????????Check data drift
iii.???????????????? Use data validation and quality checks
iv.???????????????? Incorporating human feedback mechanisms
v.??????????????????Keeping a record of the entire monitoring process
Educate and Train the Workforce - Empowering the Data Custodians
A system is only as good as the people operating it. By investing in training programs, organisations can ensure their employees are well-equipped to leverage the centralised data system, including understanding best practices, recognising potential security threats, and knowing how to derive actionable insights from the data.
In essence, while data centralisation offers myriad benefits, it has challenges. However, with clear governance, the right tools, a focus on security, and an emphasis on collaboration and education, organisations can navigate this complex landscape, turning potential pitfalls into stepping stones towards a data-driven future.
Please scroll down and click on the like button if you're enjoying this blog.
Click here to Subscribe to my weekly newsletter for more blog posts, and follow me on Medium.
See you next week. Thank you!