Understanding the value of holistic data management
Four reasons why organisations should move away from the siloed data management approach and go the holistic route.
In a world driven by data, being a data-driven organisation is no luxury – in fact, it’s quickly becoming a critical necessity to business resiliency.
Organisations are under pressure to unlock the true power of their data to become more efficient and stay ahead of the curve. Key to this is establishing a data management approach that truly adds value to the business.
My experience as a data engineer and consultant has ignited my passion for a holistic data management approach. In this article - the first of a two-part series I am embarking on - I will address how most companies manage their data and share a definition of holistic data management.
I also mention nine reasons why organisations should be using a holistic data management approach and share some insights on the first four. The remaining five reasons will be expanded on in a second article, together with what organisations should be aware of when deciding to move to a holistic data management approach.
How it’s currently being done
In my experience, many organisations follow a siloed data management approach with data isolated to be department- or solution-specific. This, however, can lead to some data challenges.
Data duplication and inconsistency within the data and across the system are likely and it will become a challenge to maintain the data integrity, and ensure consistency and accurate reporting.
Having siloed data puts restrictions on the sharing and collaboration of the data across the different departments and teams. This then hampers effective decision-making and stifles innovation.
Furthermore, siloed data management often lacks a centralised data governance framework, and this makes it difficult to analyse multiple sources, as understanding how the data links and interacts is not always clear. Thus, getting comprehensive insights from the data is nearly impossible.
A holistic view of data becomes necessary in order to make accurate, timely decisions.
Maintaining all these datasets also makes it costly and inefficient - as it is using storage as well as resource time to get the solutions up and delivering what the business needs.
Lastly, and maybe the costliest aspect of this data approach, is that siloed data management hinders organisations’ agility and responsiveness to changing business needs. It makes it difficult to integrate new data sources and adopt new technologies.
Making the move
Holistic data management refers to the comprehensive and integrated management of all data assets within an organisation to support effective analytics. It involves adopting a strategic approach to data management that encompasses all the different sectors of data. This includes data governance, data integration, data quality, data security and data lifecycle management.
In a business decision-driven world where there is a lot of data kept in different silos, a holistic view of the data becomes necessary in order to make accurate, timely decisions.
There are numerous benefits to moving away from a siloed data management approach and adopting a holistic one. Listed below are nine reasons why a holistic data management approach makes sense. I also elaborate on my views of the first four.
- Data-driven decision-making
- Improved efficiency and productivity
- Enhanced customer understanding
- A competitive advantage
- Compliance and risk mitigation
- Cost optimisation
- Agility and innovation
- Stakeholder trust and transparency
- Working remotely
In today's data-driven business landscape, organisations rely heavily on data to make informed decisions. Holistic data management ensures data is accurate, reliable and accessible, enabling decision-makers to rely on high-quality information for strategic planning, operational improvements and identifying new opportunities.
If organisations do not follow a holistic data approach and work in a siloed approach, their decisions will reflect inaccuracy and a full bird’s-eye view will not be achieved. Getting a full grasp on the data used to make business decisions in an organisation makes it critical for decision-driven solutions and knowing what the impact will be downstream and the underlying components it affects.
If an organisation can establish these potential problems that have not yet occurred, these issues can then be managed more strategically and timely.
Improved efficiency and productivity:
Holistic data management streamlines data-related processes, such as data integration, data cleansing and data access. By establishing standardised practices and tools, organisations can reduce manual effort, minimise errors and enhance productivity.
This allows employees to spend more time analysing the data and deriving key insights from it, rather than struggling with data-related tasks. Holistic data management provides a clear view of essential data that otherwise will be unreliable and scattered across the organisation.
Enhanced customer understanding:
Data holds valuable insights into customer behaviour, preferences and needs. Holistic management of data enables organisations to consolidate and analyse their customers’ data from multiple sources, leading to a comprehensive understanding of their target audience.
This knowledge allows companies to tailor their products, services and marketing efforts to better meet customer expectations, which can result in improved customer satisfaction and loyalty.
Organisations can in some on-market tools draw relationships between their customers to see the physical relationships. Establishing customer relationships can be very beneficial, especially for target marketing. To demonstrate this point, for example, an e-mail arrives in your inbox shortly before your anniversary date, suggesting a specifically tailor-made gift for your partner.
Effective data management enables organisations to gain a competitive-edge over their competitors by leveraging data-driven insights based on quality data. With holistic data management, companies can identify market trends, predict customer behaviour, optimise operations and innovate more effectively.
It is extremely important for an organisation to have a competitive-edge and to stay relevant. Data that is not holistically managed will slow down the organisation's ability to make timely and informed decisions, hindering its ability to respond quickly to changing market dynamics and stay ahead of its competitors.
With the current economic crisis - and the effect of load-shedding in South Africa - it is now more important than ever to have a competitive-edge and effective data management plays a key role in achieving this.
Do keep an eye out for my next article, as I will address the remaining reasons for investing in a holistic data management approach.
Data engineer, PBT Group.
Minette Lubbe is data engineer at PBT Group. She is a principal data engineer and analyst with over 15 years of experience within the IT sector, in different data warehousing-related roles across various industries. Lubbe specialises in analysing and planning business strategy and is also responsible for leading her dedicated team during client projects and overseeing daily solutions. She is a powerful force in the workplace and uses her positive attitude and tireless energy to encourage others to work hard and succeed. Lubbe graduated from North West University with a bachelor's degree in computer science and psychology. She has also completed her honours in computer science.
Minette Lubbe is data engineer at PBT Group. She is a principal data engineer and analyst with over 15 years of experience within the IT sector, in different data warehousing-related roles across various industries.
Lubbe specialises in analysing and planning business strategy and is also responsible for leading her dedicated team during client projects and overseeing daily solutions.
She is a powerful force in the workplace and uses her positive attitude and tireless energy to encourage others to work hard and succeed.
Lubbe graduated from North West University with a bachelor's degree in computer science and psychology. She has also completed her honours in computer science.