Decision Engineering and Big Data
We have all heard about big data and what it could do. It helps businesses get more insights about their operations, customers and competitors using data that they get from various sources.
And it would seem that everyone is already gearing up to get a piece of the big data action. More and more companies are planning to have big data strategy of some sort for their companies, while there are simply a lot of articles and talk about big data at the moment. Big data is also seen to create close to four million new jobs all around the world this year. But does it all end there?
Even with all the attention on big data, there are still people out there who claim that companies who have taken time and invested on big data infrastructure are not able to fully utilize these systems, especially in making business decisions. And that is because most businesses make the mistake of focusing on the infrastructure and the system rather than facilitating ways to make it easier for manager to make business decisions. And this is what is called decision engineering.
Simply put, decision engineering is the process of taking data and using it to engineer better business decisions. And this is seen as the next phase of big data.
Decision engineering would not be possible without the people who can make sense of the data. The industry would need more skilled people who can take care of all the data that a company gets and see how these could be used towards better decision making.Click here to read more about this article
What are the skills needed for decision engineering?
First you have to be a big data engineer. You need to know how to set up and manage any big data environment. This would mean that you should be proficient with different software and platforms such as Apache PIG, Cloud Era, Hadoop, Hive Map Reduce and others. You would need to be familiar with managing, integrating and working with big data systems.
Then you would need to be a big data scientist as well. The big data scientist should know statistical modeling as well as machine learning skills. You should know Random forest, Gradient Boosted Models, Bayesian Statistics, Collaborative Filtering, Support Vector Machines and other similar technologies. The big data scientist would also need to know how to develop advanced algorithms and even predictive algorithms. These algorithms would allow you to get actionable insights from big data, as well as accurate business insights and predictions.
These are the technical skills that you should have. But that is not all. You also need to have great communication skills, consulting and domain-specific skills.
If you are looking into big data, then you should get in touch with Four Cornerstone. On top of our services, such as Oracle consulting and Oracle software licensing resell in Dallas we can also help you get into big data and decision engineering without the hitches. Not only can Four Cornerstone assist you in getting your big data platforms and systems, but we also have the know-how to help you get the insights you need from the data that you own.
Photo by Philip Kromer.