Big Data and Advanced Analytics are creating profound new opportunities for businesses, yet very few companies are able to combine the right people, technology, data and processes to take advantage. To realize the value of big data, organizations need strategic and holistic solutions. Big Data is not just a technology initiative to be left entirely to data scientists and IT departments. It’s a strategic business opportunity that requires extreme coordination between the IT departments and the entire organization. In order to successfully execute a Big Data and Advanced Analytics strategy, companies need to ensure that the information & insights received from Big Data and Advance Analytics projects are shared across business units and functions.
Before we jump into the benefits and cautions, let’s focus on what Big Data Analytics really is? It is the process of examining large amounts of data sets to identify hidden patterns, correlations, market trends, customer preferences and other useful information that can help companies in making more-informed business decisions. Certainly, this is a key initiative for companies to get started with. So how do you begin?
- Begin by identifying the questions you need to be asking in order to set the strategic rationale for your analytics initiative
- Why do you want to do it?
- How many data-driven decisions are you currently taking?
- How much data are you sitting on?
- And what results are you expecting to achieve?
- Clearly articulating a strategy by answering the above questions help keep the organization focused.
- As an organization, you are sitting on a large amount of structured or unstructured data already. Instead of spending on new external data sets, figure out what you already have handy. Advance Analytics can help you identify some small use cases that will be a good proof of concept for experimenting with your analytics journey.
- Bring in analytical rigor through expertise, either by hiring the right talent internally or getting external support. You will need this to support a multitude of analysis, such as : predictive modeling, customer segmentation, experimental design, pricing optimization etc.
- Iterate fast – small proof of concepts will help you see results quickly. Be aggressive to identify if desired results are not being achieved and course correct accordingly.
- Keep organizational alignment on results – no amount of data projects will be helpful if your business will not use them aptly. So bring in executive support to rally businesses to use the generated data sets.
Potential pitfalls that can trip up organizations on advanced analytics initiatives include a lack of internal Advanced Analytics skills and the high cost of hiring experienced data scientists and data engineers to fill in the gaps. The amount of data that is typically involved, and its variety, can cause data management issues in areas including data quality, consistency, and governance; also, data silos can result from the use of different platforms and data stores in a big data architecture.
In summary, the decisions to undertake Advanced Analytics initiatives are not optional anymore. In the next 5-10 years, any organization not using the power of Big Data and Advanced Analytics may very well become extinct.
So don’t delay. Start thinking about your data strategy, now!