Managing Data
The old IT slogan ‘rubbish in: rubbish out’ is as true as it has ever been, and applies especially to the process of data analytics and data management.
It is a harsh reality that if your data is not as well managed as it should be then your analytics will likely be suspect and not provide the accurate information and insights modern data analytics are capable of. The reason being that your analysis will be based on poorly presented data ill prepared for accurate analytics.
So good data management and sound data analytics is crucial to your business activities.
The importance of good data management
Most if not all businesses and organisations of various sizes store a lot of raw information, but unless managing data is done properly it will not be providing the valuable insights that could improve profitability and productivity.
If your data is difficult to access, incomplete, inaccurate, contains duplicates, not ‘cleaned’ (amongst other ills) and difficult to pull together then it is not really ready for analytics. Indeed, any analytics done on data in this condition is likely to be flawed and could lead you to wrong conclusions and possibly embarking on an inappropriate strategy or other business activity.
Using easy to use and accurate data to inform your business activities is no more than your competition is likely doing, so poor managing data procedures that would prevent you doing this effectively could see you fall behind others in your marketplace.
What is good data management?
There are different ways of looking at this: it could include the whole process from gathering, storing, accessing, analysing then archiving past data or it could refer primarily to the storage, maintaining and preparation of data prior to analytics taking place.
The implications of good data management may sound a daunting prospect, but the good news is this is an area where professional data analytics consultants can help in advising and taking a proactive role in your managing data procedures.
Some elements of managing data effectively are:
Gathering – more data from multiple sources, internal and external, can give you more to base analytics on, so being able to gather data from ever-increasing sources and thus formats add to your ‘store of knowledge’.
Cleaning – ensuring your data is ‘clean’ and up to date as possible, and eradicating duplicates and other data errors.
Storing – establishing the best method of data storage based on usage such as data warehouses, data lakes and others.
Manipulation – and data wrangling, establishing a reliable system for merging and aggregating data from often multiple sources ready for analysis.
Repeatability – instituting a system for consistently repeating your data preparation regime improves accuracy, saves time and makes it easier to use data models.
Security – a constant priority, security of your data is obviously vital so solid systems and procedures should be put in place to protect your valuable information.
Unleashing the power of professional data analytics can only happen once your data management is as sound as possible.
FAQs
Can we ‘systemise’ our data management?
Yes, and it is a very good policy to adopt. If you partner up with an experienced data analytics consultancy, they should be only too pleased to help you set up a data management system to ensure your data is gathered effectively, stored in the best way possible, clean, accurate, secure and manipulated soundly ready for analytics.
Once your data management system is initially set up then it is ready to run month in month out to ensure the best possible quality of data for analytics purposes.
What are the implications of poor data management?
At best you will never be able to make the most of your hard-won data in terms of learning how sales campaigns went, understanding your customers better and conducting the most effective stock control.
At worst you may come to incorrect conclusions and make wrong decisions and misjudge the direction your business should be headed. You could annoy and alienate customers and prospects by, for example, sending duplicate communications or promoting products and offers they are not relevant to them.
Ultimately, you will likely fall behind those of your competition who are using a coherent data management system and working with accurate information.
Is moving to structured data management daunting?
It need not be with the right help from experienced data analytics consultants who, along with analysing your data to best effect, can help you institute a sound data management system that will serve you well going forward.
More and more data is being gathered so your ability to store and work with it efficiently and effectively will lessen if your present managing data procedures are weak; an investment in a strong data management system will pay off handsomely in likely increased revenues and productivity.