Operating a successful data management strategy

Businesses, charities, local government, educational establishments, the National Health Service (NHS); the list could go on, these organisations have all seen the knock-on effect of, if not been directly affected by, cyber-attacks, including those that have made headline news recently.

 However, cyber attacks are just one of many challenges that organisations face daily; successfully managing data and implementing strategies around these challenges is an arduous task and there is often no ‘one shoe fits-all’ solution.

>See also: The importance of managing data

 What is a data management strategy?

A data management strategy (DMS), refers to a set of policies and procedures that an organisation follows to successfully keep control of and protect data from all threats and challenges. A DMS needs to bear in mind many aspects and each network, site or organisation is likely to have a different strategy. Factors to bear in mind may include:

• What sources of data are there?

• How much data is there (new and existing)?

• How long should data be retained for?

• How valuable is the data?

• Who needs to access data?

 How to pick a data management strategy to fit your organisation

The first step in setting a DMS is to understand the aims of the DMS and to have a full understanding of the data/network that needs protecting.

While undertaking a full audit can be time-consuming, it will give valuable insight into data, how to protect it and could shine a light on any changes that should be made immediately.

>See also: Enterprise storage in 2017: trends and challenges

With data growing at such an exponential rate, an estimated 40% year on year, keeping control of data and where it is stored is not easy.

For many organisations, data is sprawled across multiple platforms and systems, including for public and private clouds and a data audit can help to identify where data is located and allow centralisation and more effective management.

Once a data audit has taken place, data must be categorised and placed into its correct stage in the data lifecycle, this will help to identify further how the data should be protected and whether it needs to be retained, archived or deleted.

• The data lifecycle is useful to examine in determining when data has been created and how long it should be retained before it is deleted.

As different data sets and sources will have different values and retentions, your DMS needs to take this into account.

>See also: Cloud data management: data protection

Similarly, the size of an organisation and IT spend should be considered when planning to implement strategies or changes to your data management approach.

While there are solutions available that can centralise and automate the whole of an organisation’s strategy, these are likely to come at a premium and may not be suitable for all – they may also have functionality that is unnecessary for your business.

 Centralising data

To help protect and manage data, it is important to know where it is and if possible reduce the spread of it.

Centralising data will give you more control, allow you to set policies around who can access sensitive information and reduce the risk of an internal data breach.

In addition, with data in less locations there are less avenues for external data breaches in the forms of malware or hacking to occur.

>See also: The value of data driving business innovation and acceleration

 Automating data management

While policies and procedures need to be implemented, automation can be a vital tool to ensure this process happens quickly, works effectively and is free from human error.

Increasing the number of data management processes through a DMS could have a negative impact for your organisation if the strategy is not followed effectively as it may become complex and time-consuming.

 Measuring success

A successful data management strategy, should simplify processes, increase the protection and visibility of data and help to drive IT efficiency.

>See also: Artificial or not, intelligence requires cleaned and mastered data

When deciding on strategy, measurements should be taken as a benchmark and then used as KPIs for regular reviews of the effectiveness of the strategy.

• KPI / key performance indicators are measurable values that demonstrate how effectively a business strategy is working.


Sourced by Paul Evans, managing director at Redstor


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Nick Ismail

Nick Ismail is a former editor for Information Age (from 2018 to 2022) before moving on to become Global Head of Brand Journalism at HCLTech. He has a particular interest in smart technologies, AI and...