Do you need a data strategy?

Three "A"s to improve your data management

In previous blog posts I’ve discussed the benefits of creating an L&D dashboard and the need to keep historical data, including training data. But a dashboard is only as good as the data behind it. Bad data with visual impact is still bad data. And worse, it will lead to bad decisions without anyone realising why. 

A well-thought-out data management strategy is the necessary step before reporting. It will save you time, money, and will improve decision-making. 

Small and medium sized businesses (SMEs), and departments within large organisations, can all benefit from managing their data in a structured way. A data strategy provides a framework that makes it easier to discuss the costs and benefits of data management. 

In this article, I’m going to discuss how to develop a data strategy to keep your data accurate and trustworthy. 

The basics

There are some basic principles to think about, regardless of what type of business or department you work for. These are the three “A”s of data management:

1. Accurate

2. Available

3. Adheres to the rules

Accurate

Data that doesn’t contain errors sounds simple enough, but mistakes creep into data in all sorts of ways. Incorrect dates, spelling mistakes, the wrong person or the wrong course, etc. Each individual error might not be important, but as you amass more data it all adds up. Whether you are using dashboards to monitor progress, create insights for strategy, or preparing for AI, you need a solid data foundation. 

For data to be accurate it must also be complete. It needs to include all relevant time periods, parts of the organisation, or relevant data. That often means thinking about where data is stored. You are likely to have data in relational databases such as SQL Server, or Oracle, often used as back-end data stores for LMS systems, accounts systems, production systems, etc. Other data will be semi-structured or unstructured, such as data in spreadsheets, Word documents, emails, training evaluation forms, or PDF files. 

Available

Availability means ensuring data is easily accessible to those who need it, when they need it, and in a format they can use. 

1. Granting access to those authorised to use the data and restricting access to those who shouldn’t have access.

2. Providing user friendly data models that can be used to create dashboards or for self-service reporting.

3. Storing data with appropriate redundancy safeguards. Data can be lost either by human error, hardware failures, or other disasters. 

4. Providing training so people know how to access the data, and what they can and cannot do with it.

Adheres to rules

Data rules and regulations come from both inside and outside the organisation. 

Compliance regulations such as GDPR require organisations to safeguard personal information, with heavy penalties for those who do not safeguard sensitive data.

Within your organisation you may have guidelines that define which roles have access to what data to ensure private data stays private. 

Think about who owns the data and who is responsible for safeguarding it. Use metadata (data about data) to identify different types of data within your organisation so you can put policies in place to manage it. 

Creating your data strategy

Get your team together and start the discussion. Identify a project that will provide immediate business benefits, then:

1. Identify your key data sources.

2. Agree who owns and manages each data set.

3. Identify and implement quality control measures.

Data management is the necessary first stage in communicating generating data insights and making data-led decision-making. Azure has a range of data governance, storage, and redundancy options to help you modernize your data management whilst improving accuracy, availability, and adhering to rules. 

If you want to improve your data management let’s talk about how you can get your data in better shape. Get in touch for an initial chat about what you want to achieve.