November 8, 2013
Everyone has a different explanation of big data and what it can mean for organizations. With so much information, it is easy to become confused to perpetuate the wrong information. So let’s dispel some of the most common myths about big data and its strategies.
1. Big data is new
90% of the available data has been created in the last two years and the term big data has been around 2005, when it was launched by O’Reilly Media in 2005. However, the usage of big data and the need to understand all available data has been around much longer. There are a lot of examples of companies that were into big data before it was called by that name. A well-known example is Walmart that has been using data analytics already for many years.
2. Big data is just hype
Big data is a transformative trend that will mean a paradigm shift in all industries for all companies, big or small. The amount of data will only grow in the coming years and all that data can be turned into information that can be used to improve organisations in many different ways. Already, companies that have developed and implemented a large data strategy financially outperform their peers by 20%. This will only increase and companies that will not move into the direction of big data most probably will not be able to survive in the future.
3. You need to have a lot of data to talk about big data
Big data does not necessarily have to be a lot of data. Although Volume is one of the three V’s that is generally used to describe big data, it is definitely not a requirement to have a minimum of for example a Petabyte of data. Especially the combination of different data sets provides a lot of insights and this can also happen with smaller data sets. Combining company data with social data and public data can give a lot of insights as well.
4. Big data is only for large corporations
A small business has to look differently at big data, simply because less data is created. That does not mean however that small businesses cannot develop a big data strategy. Especially when small businesses start combining various data sets they can also obtain the insights that large corporations achieve with big data. It will however probably take a bit longer before small organizations will start to see the benefits of applying a big data strategy.
5. You need to hire a big data scientist to start with big data
There are many big data startups that offer innovative tools for companies as a SaaS or DaaS (Data-as-a-Service) solution. For each aspect of big databases, (processing, storing, analysing, visualizing) there are different startups that offer such a solution and therefore an innovative tool for small businesses. For these solutions there is no need at all to hire an expensive big data scientist or analyst.
6. Big data strategy is an IT responsibility
Quite often, it is seen as an IT matter. After all you need hardware and software to implement a big data strategy. It is true that the hardware and software need to be developed by highly skilled technical big data employees (in-house or via big data startups). This is nothing strange, as the required IT of big data is different from what we have had so far and therefore sharing information about it is important and valuable.
However, big data strategy needs better inform business decisions. The strategy could be “to increase customer satisfaction” or “to increase revenue” or “to improve the operational efficiency” and the route to achieve that strategy could be big data or any other solution for that matter. If the strategy is “to increase customer satisfaction” it would be strange to define it an IT matter or have the IT Director be the sponsor.