In today’s world, businesses and organisations are struggling to cope with the ever-increasing amounts of data that is being made available to them. Worst still, there’s plenty more where that came from. We’re now seeing the advancement of new technologies to include the likes of IoT, where networks of physical devices and other objects embedded with electronics, sensors and software connect and exchange data 24/7. Experts have predicted that by 2020, annual data production will have increased by 4,300%. In reality, if you are struggling to cope with the growing expanses of data in today’s world, you need a plan and you need a plan promptly.

Organisations believe that data is a valuable commodity, and we agree, it is. But because data is a valuable commodity, we hoard it in the hope that one day we can learn from it and drive business decisions. Days, months and even years go by, but the data remains untouched.

Unlike a precious antique that we hoard for good reason whilst its value is increasing, data has a sell-by date and at some point, soon, the data will become outdated, incorrect and unusable, but companies are still prepared to pay to store the data. But, has there been any consideration as to why the data is being stored in the first place? Does it even align with the overall objectives of the business? If data is stored without reason, it isn’t needed and therefore, won’t be updated, meaning big data is turning to bad data, as a result of storing vain data.

Often, this is where business intelligence and analytics tools often get a bad rap. These mission critical tools rely on a constant supply of clean and correct data in order to produce information and insight that can help drive informed business decision making. When that information is delivered, if it isn’t correct, guess who’s getting the blame? It’s the business intelligence tool, and this shouldn’t be the case.

We demonstrate this in our iceberg methodology. Above the waterline, you have your technology, your business intelligence tool. But, underneath the waterline, this is where your data lies. In summary, if your data is incorrect, or inapplicable to your business, the insight that your business intelligence tool is providing will be, too.
So, to turn this around, you need to construct your data strategy, and we are going to guide you through this process, below.

Your data strategy should comprise of five key components and if constructed properly and thoroughly, will help to ensure that the right data is managed and used like an asset.

5 Key Components To Your Data Strategy

Collection and Cleansing

  • What data is crucial to the running of your organisation and which data is not?
  • Is there a process for updating the data and how frequently does it need to be updated?
  • How does the data align with your organisations business goals? If the data does not align, what reason is there for collecting the data?


  • Silos of data are often controlled by an individual department or business function. Consider how you plan to share the data between the different silos in your business in order to join the dots.

Storage and Accessibility

  • Consider what data is crucial and might need to be accessed at a moments notice. Should it be made available in real time?
  • Should you be using a data warehouse and how should the data be stored? E.g. cloud or on-premise.

Insights and Data Analysis

  • Consider how you plan to analyse the data and convert raw data and information to actionable insights. Are you going to use a business intelligence or analytics tool?
  • Ensure you are not just measuring vanity metrics. Ensure the data is converting into information that can be acted upon.

Governance and Security

  • How do you plan to secure your data and protect it from breaches?
  • What policies and legislation do you need to be aware of?


And finally, before storing any data, always ask “what are we trying to achieve by storing this data and how does it align with our strategy”? Don’t fall into the trap of collecting and storing vain data. Collect and store applicable data that can be used to drive real, positive business change.

April 18, 2018