How to Achieve Big Success from Big Data [INFOGRAPHIC]
Big Data offers huge potential for any organisation in any industry. This is what always has been said and the past years Big Data has been hyped enormously. However, a new study carried out by Accenture revealed that companies with Big Data experience are satisfied with business outcomes and that Big Data is revolutionizing the way companies do business.
Big Data offers huge potential for any organisation in any industry. This is what always has been said and the past years Big Data has been hyped enormously. However, a new study carried out by Accenture revealed that companies with Big Data experience are satisfied with business outcomes and that Big Data is revolutionizing the way companies do business. In fact, 92% of the companies surveyed are fully satisfied with the business outcomes of their Big Data initiatives. In addition to that, 94% of the companies surveyed reported that their implementation is meeting their needs. Starting with developing a Big Data project therefore pays off for organisations.
Of course, that is not a surprise as combining different, external and internal, data sources provides you with great insights. Implementing a Big Data project is not easy however. On average such a project takes 18 months to complete and offers ample opportunities to fail. According to the Accenture research the top five challenges for a Big Data strategy are security, budget, lack of talent to implement, lack of talent to run and integration with existing systems. These challenges are quite straight forward:
- Security: there have been many different data breaches and combining different data sources can be difficult and complex to keep secure for the outside world. Too often large companies have been hacked and personal data has been stolen. Getting this right is difficult;
- Budget: planning the budget for a Big Data project is difficult because of the many unknowns. Which technology to use, how to use it, what to implement on premises or what to use from the cloud. All questions that impact your budget;
- Lack of talent to implement and run: This is a major issue for any organisation. Big Data talent is scarce and therefore expensive. Companies that want to move forward with Big Data should think of this carefully. There are several options available ranging from hiring consultants, working with a SaaS solution or training your own staff;
- Integration with existing systems: many organisations have legacy systems that need to be incorporated. In addition, many organisations have their data in silos across the organisation. Getting this fixed and integrating new Big Data technology with existing systems is a challenge.
The survey also shows that larger organisations are more positive about the results of a Big Data project than smaller organisations. This does not mean however that Big Data is less interesting for smaller organisations. On the contrary; smaller organisations might have less data, but Big Data is not so much about the volume of the data at hand, but a lot more about combining different data sets. In order to get results from Big Data, you do not need petabytes or more of data. Instead, it is all about combining data sources that provide you the insights. As mentioned before, I like to call this Mixed Data.
In the end, Big Data, or Mixed Data, offers ample opportunities for organisations. That’s also revealed once more by this survey. 89% of the businesses surveyed believe that Big Data will revolutionize the way business is done. Therefore, it is wise to start with you Big Data strategy as soon as possible.
I really appreciate that you are reading my post. I am a regular blogger on the topic of Big Data and how organizations should develop a Big Data Strategy. If you wish to read more on these topics, then please click ‘Follow’ or connect with me viaTwitter or Facebook.
You might also be interested in my book: Think Bigger – Developing a Successful Big Data Strategy for Your Business.
This article originally appeared on Datafloq.
You must log in to post a comment.