Below are six of the major data analysis challenges together with some potential solutions.
1. Quality of Data
What comes out is always a reflection of what goes in, so reliability and quality are vital. Data that is inaccurate, incomplete, inconsistent or duplicated can easily lead to incorrect insights and poor decisions.
Some solutions to help with this include data validation, data cleansing, data standardisation and data governance.
2. Access to Data
Many organisations have data scattered across numerous different systems. Some of it will be structured, some will be unstructured and some semi-structured. This poses challenges for consolidation, analytics and artificial intelligence.
The key ways to deal with this issue are having a central repository for all data, or using APIs to connect everything directly to analytics apps.
3. Poor Visualisation Methods
Using incorrect visualisation methods or including too much data can easily lead to incorrect conclusions. Effective visualisations are tailored to the relevant audience, have a clear purpose and are kept simple.
4. Data Privacy and Security
Careful attention must be paid to who has access to the relevant systems to view or retrieve data. To overcome such challenges, organisations need to identify all the types of data they use, develop a classification matrix and then establish appropriate data security controls.
If you feel that you need outside help, there are a number of specialists in this arena. A data analysis company such as shepper.com will be able to provide you with advice and services.
5. Too Many Different Analytic Tools
Many organisations end up with a mish-mash of unconnected tools for various different parts of the analytics process. To avoid this, there needs to be an organisation-wide strategy for collecting, storing, and analysing all data. And there needs to be a unified approach to all analysis.
6. Cost
Any sort of data analysis will require some investment in systems and staff. It can be hard to predict how and when this will pay for itself.
Costs can be minimised by opting for a cloud-based architecture and using existing staff and familiar systems.
