Data is currently the most valuable asset available to organisations and marketers, aiding in informing strategies, decisions, and maintain the competitive edge. Today, it’s more freely available, ineffective, and vast in amounts than ever before.
To take full advantage of your collated data, as well as to ensure overall data security, quality, and confidence, it’s essential to employ high-quality, optimised, and efficient data management practices.
What is data management?
In its simplest form, data management is the overarching concept of storing, planning, retrieving, archiving, and other practices relating to collated data, enabling BI projects and implementation. An optimised management framework can bring a wide range of benefits to any organisation, ranging from alleviating any potential bias to establishing a scalable and consistent data infrastructure that adheres to compliance policies.
Challenges of data management
Current organisations wishing to implement data management may encounter a variety of challenges that threaten to destabilise data strategy and consistent approach. Some of these challenges include:
- Creating clear communication of data management concepts throughout an organisation.
- Integrating specialised software that coincides with current architecture.
- Reducing and seeking to eliminate pre-established harmful data silos.
- Struggling to handle the sheer volume of pre-collated data.
- Establishing an overarching data strategy for future-proofed consistency and flexibility.
As market-leading experts in data management, strategy, and storage, we’ve curated the essential principles to ensure your data management efforts are successful:
- Utilise a Data Warehouse.
- Introduce specific requirements for data storage.
- Create a security system for peace of mind.
- Maximise the use of your data.
Utilise a Data Warehouse
A Data Warehouse is a data management system that allows businesses to perform BI and Data Analytics efforts. It achieves this by acting as an overarching store that uses ETL processes to consolidate, collate, and file large amounts of structured data from a variety of sources.
This ensures that data collected from a wide range of sources is stored in a consistent and uniform structure that allows for easy loading into BI tools to access previously unreachable insights. A Data Warehouse is also future-proof and scales in size easily as collected data continues to grow and expand.
Creating a clear, overarching view of your data also allows organisations to eliminate the risk of a potential bias that skews strategy. This bias is often introduced through important data being excluded from BI efforts or other analysis tools. This may cause slight misunderstanding in minor events but may be catastrophic – such as shifting the allocation of funding due to referring to important or incorrect sales figures.
A Data Warehouse is often an essential tool in any organisation wishing to optimise its data strategy, introduce BI efforts, and maintain the competitive edge with data-driven insights.
Introduce specific requirements for data storage
Low-quality data can bring a wide range of consequences to any BI and analytics efforts, such as missing potential strategic opportunities and loss of potential revenue.
Introducing specific standards and criteria that data must achieve to be stored reinforces consistency and ensures that all collected data is high-quality and reliable to a standard. When these requirements are communicated throughout the entire organisation, it also serves to reinforce a data-driven culture.
Examples of these requirements for data storage may include:
- Communicating the need for regular audits of stored data to ensure quality.
- Establishing conditions for ongoing quality and maintenance of data until it is no longer needed.
- Ensuring that all data is relevant and complete, without missing fields or information.
By creating and communicating the need for high-quality data in management, organisations can ensure that any and all data that may be potentially used is trusted and reliable, reducing the margin of error and ensuring trusted insights based on confidence and reliability.
Create a security system for peace-of-mind
Data security is highly important to ensure successful ongoing data management and operations. A clear security system decreases the chance for damaging opportunities. Two common risks which a clear and efficient security system can aid in protecting valuable data against is data breaches and corruption.
Data breaches are becoming an increasingly developed and advanced industry. In 2020, the average cost of a data breach in the US was £2.9 million, with breachers targeting all sectors and tiers with equal emphasis and hostility. An advanced security process such as UEBA consistently monitors and predicts attacks based on previous behaviour and specific vulnerabilities, providing reassurance and peace of mind.
Data corruption is another common and devastating possibility that may potentially disrupt operations at all levels and prevent access to crucial insights, often introduced through faults in software or viruses being inserted. To protect datasets, we recommend utilising both security systems and regular backups, either to the Cloud, to physical hardware, or both for maximum confidence.
Maximise the use of your data
Data management efforts are pointless without effective use. Incorporating the use of data into all operations promotes the propagation of a data-driven culture. This is a core tool in ensuring that data management principles are adhered to and valued for consistency, promoting efficient insights and giving organisations valuable insights through trust in confidence and approach.
As trusted experts in Business Intelligence and analytics, we work alongside our partners to establish short and long-term goals, understand and revise the underlying architecture, and aid in incorporating successful data management and strategy projects to achieve truly data-driven insights.