More and more companies are beginning their Big Data expeditions in 2015, with many businesses experimenting with pilots to see how they can leverage Big Data in order to reform decision making. Therefore Wolf recommend these do’s and don’ts be considered as part of your strategy:
1) Do include all areas of the business in you Big Data strategy:
The point of Big Data is that it’s BIG! It’s not isolated, but all inclusive in order to leverage those huge volumes of data to gain insight into your customers, processes and events. When properly executed, Big Data strategies can have a huge impacts on the effectiveness of business strategy.
2) Do assess all delivery models for Big Data:
Petabytes of data are often stored and managed in data centers. However this isn’t your only option. The pace that technology is changing means that it’s possible and often necessary to adopt cloud computing storage. Evaluate the type of services that are cloud based and determine which will offer you the best performance for your needs.
3) Do think about your traditional data sources:
Information held in traditional data warehouses is just as important as the value found in Big Data analytics. Data involved in the traditional data warehouses often stores vital information on the way your company operates and it’s crucial to be able to compare your results to these core benchmarks.
4) Do expect and plan for consistency in big metadata:
Once a set of metadata has been analysed it’s likely patterns will emerge amongst the data. These data patterns can now lead your organisation to begin analysing a new issue in depth. Keep in mind that this data might come from customer service or social media environments that have not been cleansed. Before you trust the data, you have to make sure that you are dealing with consistency of metadata so that you can bring this information into your organisation and analyse it in cohesion with the data from your systems of record.
5) Do distribute your Big Data:
It’s highly likely that when dealing with Big Data you will require more than just a single server. Distributed computing techniques can help to effectively manage the differentiation, volume and required speed to manage your data.
6) Don’t narrow your opportunity for discovery by only selecting a single approach to analytics:
Investigate the wide variety of approaches and techniques that are available to support you. Experiment with these solutions so that you gain a greater scope of what is achievable. A lot of important technologies are available, such as text analytics, predictive analytics, streaming data environments, and spatial data analysis, that may be important for the job you are trying to accomplish.
7) Don’t go big with your data before you are ready:
Your company’s Big Data potential is something you should be rightly excited by, but don’t run before you can walk. Begin with a pilot project that will allow you to gain some experience. You need to work with experts who can keep you from making mistakes because of inexperience.
8) Don’t forget to integrate Big Data:
Isolated Big Data sources are far less effective than integrated ones. Trends in technology point towards easier synthesis of the results of Big Data with other sources. therefore focus on analysis, but don’t neglect integration.
9) Don’t neglect managing your Big Data securely:
Security and governance is just as important in analysis as it is in traditional data management environments. When conducting analysis of several petabytes of data the chances are you won’t immediately mask sensitive or private information. Ensure that you have all the necessary licenses required for third-party data sources, ensure you are following governance rules and are securing data so as to not put your business at risk.
10) Don’t overlook the need to manage the performance of your big data:
Big data demonstrates that people are able to make use of more data than ever before at a faster rate of speed than was possible in the past. This capability to gain more insights is a huge benefit. If that data isn’t managed in an effective way, it will cause huge problems for the company. Therefore, you need to build manageability into your road map and plan for big data.
To learn more about what Wolf can do with your Big Data visit our Business Intelligence page.by