How to use Big Data to your company’s advantage

Big Data is all about technology and innovation. High speed networks, data sets, data marts, databases, data warehouses and softwares are all very important – these are the technologies and the technical innovations that make it all possible. Lots of companies are squandering all their investment in Big Data. They are trying to make Big Data a technology-driven vacuum.
Managers often ask themselves “Who owns Big Data?” and from the point of view of the IT department, this question is a bit foolish. We already settled the fact that Big Data is mostly about technology and innovations and that all the tools like databases, networks and software applications are what makes it possible. But this doesn’t mean that we should make it a technology-driven vacuum. Here is why we shouldn’t squander with it.
The means to an end:
Yes, the technology that surrounds Big Data is truly amazing and innovative, but in the end, it’s just the means to an end. I say this because I realize that all this technology and technical innovation is just a system of tools in the data driven decision making process. This technology is offering us the ability to process huge amounts of data in real time for decision making purposes. But this is a technical process which is not solving any business problems unless it gets insights from the analyzed data or if your company is getting valuable actionable insights.
The IT staff definitely plays a critical role in the process of analyzing and sorting Big Data. And since its nature is to give real time insights, it demands a high level of support – support from the IT staff and technologists. That’s why when it comes to Big Data, it is like we discovered the oil, but we haven’t built the cars yet.  
There are still very few people who are equipped to understand the data and the statistical machines that are used to produce actionable insights at an intimate level. This is why we cannot use all the available data to gain insights. Companies are trying to implement Big Data at an enterprise level, so every department could make use of the data, but I believe that this is a wrong approach, at least for the moment. Watching from outside, it looks like all the departments are fighting for “ownerships” and this, my friends, is a wrong tactic. Instead of doing so, all the departments should “go along with the Big Data party” and work together under the supervision of those with technical competence and flexibility. The IT department usually has a talents for Big Data project management.
Gathering and hoarding:
Business Intelligence and Data sets have been around for 50 years, since the computer was invented. (Or very soon after). Business Intelligence has been used to  analyze and interpret data, while data sets, data warehouses and databases were used for storage. Data was stored in databases and business intelligence used tools like reporting tool, spreadsheets and dashboards to analyze this data.
The problem came when the process of gathering the data has become something more like hoarding of data. And BI has started to disappoint with its inability to access and analyze all the data. A reporting tool works only with structured data, but the amounts of data were (and still are) so huge, that it became hard to store it and structure it at the same time. The technology around Big Data makes it easy to gather a wide range of information, but software applications like reporting tools were not fast enough to analyze it.
Don’t get me wrong: a reporting tool is still a useful tool in any company. It can be used to analyze the structured data and to create reports over that data, but for Big Data a different type of tools was required. So Business Analytics stepped out with tools provided by BI developers, tools like OLAP and data-mining. It still is very hard to store all that unstructured data, but it is even harder to analyze it. But technology is continuously developing and we hope that it can keep up with all the data that is being gathered. 
Rules:
In order for a business to be successful, it needs cross functional teams. These are teams made out of members of every department who work together and have the same purpose. Oftentimes, companies don’t pay attention to a matter like this, which is problematic. Each department has its own way of working, its own tasks and its own rules and when they try to work together, they bump heads. This is why a “cross-functional teams” relationship is required. Having teams with members from every department and data analytics experts can play a key role in the Big Data initiative. It can also contribute to the success of a company.
A complementary attitude is what a company needs – a complementary technique between Business Intelligence with its reporting tools for past insights and Analytics as predictive insights - and a complementary technique at departmental level.