Big Data is here to stay and it is having a profound effect on businesses and societies. But, there are still so many organisations that have no clue about what Big Data is. Big Data means different things for different people, organisations and industries. While it is true that Big Data has different advantages and possibilities for different organisations and industries, the definition of Big Data can and should be the same for everyone. Especially because that would be beneficial for the acceptance, and therefore application, of Big Data, resulting in more innovation and economic growth.

There are 7 V’s that describe and affect Big Data and your Big Data Strategy. Apart from Volume, Variety and Velocity these are Variability, Veracity, Visualization and of course Value. These V’s provide a guideline to what the different components of Big Data are and what the different aspects of a Big Data strategy are.

In the past years, many organisations have launched and are enjoying the benefits of successful Big Data projects. However, starting with Big Data is more difficult than it seems. It requires a different culture, perseverance and a shared understanding of what Big Data is.

Big data isn’t so much about the volume of data as it is about combining and analysing various, internal and external, data sets to uncover new, valuable insights that can move your organisation forward. Research has shown that 55 percent of Big Data projects are abandoned or fail to achieve their objectives.

So how should organisations start with Big Data? Well, I have developed a Big Data Roadmap that will help you move forward and this roadmap consist of the following steps:

Management buy-in. Having management buy-in from the start is essential to the success of any Big Data project. Big Data projects typically take up to 18 months to complete and management buy-in ensures that a Big Data project will not be abandoned before any results are realized.

Multi-disciplinary staff. Data tends to remain in silos across organisations, within different departments and with different owners. A multi-disciplinary team can determine the different criteria for selecting the first Big Data use case to turn into a proof of concept.

Start small. It is vital to start small, fail fast, and fail often. Learn from the failures and slowly evolve the Big Data proof of concept. During this process, it is very important to share all that is done in the proof of concept with the entire organisation. Big Data needs a different culture, in which all employees recognize the implications of Big Data and turn to data in their decision-making.

Don’t Let Your Customer Become The Victim

When you deal with Big Data, privacy can become an issue. There are so many examples available in the market where organisations failed to protect the privacy of their customers. Unfortunately, data breaches resulting in theft of sensitive information, occur regularly. Therefore, in order to protect your customers, it is important to adhere to four ethical guidelines when dealing with Big Data:

• Transparency. Be open and clear about what you do with the data, now and in the long run.
• Simplicity. Make your strategy understandable for everyone, including the digital immigrants.
• Privacy. Everyone in your organisation must protect customer data.
• Security. Do everything necessary to prevent data breaches.

Value Creation With Big Data

Big Data has a lot to offer for organisations. Although a Dig Data strategy is not easy to develop and implement, the earlier you start working on it the better your chances are to outperform your competitor. There are many different benefits of Big Data for organisations, ranging from customer knowledge and risk reduction to optimize your sales:

• Better knowing your customers enables you to reach out to your customers with the right product/service/message at the right moment via the right channel;
• Mitigation of risks and reduction of fraud due to combining different data sets and using pattern analytics to detect anomalies that could indicate fraud;
• Optimization of your supply-chain because every player within the supply chain has all the data to deliver the right products at the right moment in time;
• Predicting future sales by analysing sales data of time and location and combining it with external data sources such as the weather and news.

A Wide Range Of Big Data Startups That Can Help

As may be clear by now, Big Data offers a lot of value, but unfortunately it is not very simple to implement a Big Data strategy. However, in the past few years we have seen the rise of hundreds of Big Data Startups that are here to help. These companies, from all over the world, have developed technology that can help you get the insights you are looking for without the requirement to hire a group of data scientists. Quite often they offer a cloud-based solution that will do the work for you and there are Big Data Startups in any field within the Big Data space; ranging from visualization tools, to pattern detection algorithms or new types of databases.

Big Data is here to stay and in the coming years we will see many new Big Data applications that will help organisations make the most of their data. Not moving ahead with Big Data is not an option, so starting today will give you a competitive advantage. Therefore, don’t wait any longer and start creating value with your data today.

Author: Mark van Rijmenam

Profile: Mark van Rijmenam is Co-founder and CEO of Datafloq. Datafloq is the One-Stop Shop for Big Data, creating the Big Data ecosystem by connecting all stakeholders within the global Big Data market. He is an entrepreneur, a well thought after international public speaker and a Big Data strategist. He is author of the best-selling book Think Bigger – Developing a Successful Big Data Strategy for Your Business. He is co-founder of ‘Data Donderdag’ a bi-monthly (networking) event in The Netherlands on Big Data to help organisations better understand Big Data.