1. Do involve all business units in your big data strategy:
Big Data can never be an isolated activity as it is the way which is leveraged by businesses for huge volumes of data to learn more about customers, processes and events. If Big Data is executed properly, a Big Data strategy can have huge impact on its effectiveness. Business units can gain significant value if they are involved into the Big Data process.
2. Do evaluate all infrastructure models for big data implementation:
For any Big Data initiative, volume of data and its management is a major concern. The only solution to this problem is using data centers. Cost parameters should also be considered before selecting and finalising any storage service. Cloud services are mostly preferred for Big Data but cloud environments should be evaluated first to determine which is the most suitable one. Storage is one of the most important components in any Big Data implementation and this factor should be extensively evaluated in any Big Data project.
3. Do enrich Big Data to gain context about your customer:
Data can be supplemented with more information from a marketing perspective. If data is coupled with more information, then marketers get a better angle of customers' lives, wants and needs. Marketers need to look beyond sales and marketing data to get a clearer picture of the customer front. Data should be enriched with Web data, social data and other information which are derived from sales and marketing.
4. Do plan for consistent big metadata:
If a complete analysis is done of a massive data set, then it's possible that you will come up with that data which matches a pattern. This set of data can lead an organisation to begin analysing a new issue. This data might come from customer service sites or social media environments and before you trust any data then you have to ensure that you deal with a consistent set of metadata and analyse it with the data from your systems of record.
5. Do distribute the data:
The volume of data is a major concern if the processing environment is considered. As Big Data has huge volume of data, processing on a single server is not possible. If there is a Hadoop environment then there is a solution. Hadoop is a distributed computing environment which runs on commodity hardware. It also gives power of faster processing on multiple nodes.
6. Don't focus solely on collecting Big Data at the expense of quality:
Data collection should always be strategic. Pulling data without any plan is a very confusing thing. There should be a plan and a goal. Big Data is less about collection and more about if the information is really helpful for the customer and the sales purpose. It's not about all the data, but it's right data which matters.
7. Don’t rely on a single approach to big data analytics:
There is much hype around technologies like Hadoop and MapReduce. There are lots of technologies available like text analytics, predictive analytics, streaming data environments and spatial data analysis. First investigate the variety of technologies which can support you and then experiment with the technology solutions which can make you successful.
8. Don't start large big data initiative before you are ready:
Start with small steps for any Big Data initiative. Start with pilot projects to gain expertise and head for the final implementation. Potential of Big Data is very impressive but the real value can only be achieved if you reduce mistakes and gain more expertise.
9. Don't ignore data security:
Data security is a huge consideration in Big Data planning. Security needs to be strictly implemented and after some processing you'll get a subset of data which provides some insight. At this point, data security becomes essential and the more data is processed, the more valuable it becomes. This is finely tuned output data which must be secured and data security must be implemented as a part of the Big Data life cycle.
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 at a faster speed and it will gain more insight too. If data is not managed in an effective way, then it may cause huge problems for the company. You need to build manageability into your road map and plan for Big Data.
