How Big Data may be useful to your business. Interview with Madalina Burghelea.

We interviewed Madalina Burghelea specialist in Big Data, the new “science” that collects, manages and organizes the vast amount of data generated with the new technologies to make the best decisions at all times. Madalina is professor of Master in Big Data & Data Intelligence of INSA, and tells us a little about what they are about these concepts and their relevance.

1.-What is Big Data?
Big Data is finding applications using unstructured data, which are generated each time. Basically it is just opportunities to extract relevant information in this large volume of data being handled. For example, do data mining to find the probability that a consumer will change by a competing brand.

2.- What kind of data are we talking about?
We’re talking terabytes of unstructured data generated as content users or monitoring. An example would be online shopping and resort recommendation system behind the platforms. They are processing a large volume of data based on the user profile and the behavior of similar users, where recommendations based on previous purchases are made.

3.-What has changed by comparing the volume of information to be had on the profile of buyers and habits of a few years ago?
The difference is that now you can study user behavior in detail and personal recommendations can be made only by studying their data. A large volume of properly studied and analyzed data can help us sell more effectively.

4.-I mean, that today the problem is not a shortage of data, if not “how” sort to be useful …
Exactly. There are many details that we can lose focus. The problem is to extract data or have more data, the problem is to use them efficiently.

5.-What techniques or tools are needed for that?
As we work with very large data volume, No SQL tools help much in processing. Moreover need efficient visualization tools and powerful tools for data mining and predictions.

6.-What benefits can bring the appropriate data management for businesses?

You can better understand your customers, make personalized recommendations based on previous purchases, study in real time what they say about your product or your brand.

7.-Are there significant differences (besides the amount) in data management in large companies or multinational compared to SMEs? What?

The difference is between the need to use data from a large enterprise and small. A large company needs to study the market, each of its products, sales and works more structured processes and data. A small company needs more information on advertising and should verify anytime social networks for immediate feedback. To do this, work with external or social networking data, unstructured data but with much potential.

8.-To be a specialist in Big Data is it necessary to have some prerequisite studies?

If you’ve ever had to work with data, it is sufficient to understand the need behind the program. From engineers to administrative profiles, everyone could ever have problems to process and understand data.
Engineers can implement their own applications and business profiles may find applications which can develop systems.
The Master in Big Data & Data Intelligence is adapted to all profiles who want to work efficiently with data and information. It is also important to have a lot of creativity for Big Data applications on data that apparently does not seem to be useful.

9.-What career are students of this specialization?

They can work as consultants to Big Data and Business Intelligence or Data Scientists. Furthermore, as the training is oriented innovation and creativity, you can see online data applications and assemble their applications and businesses.
My wish for my students is gradually able to ride their business and find innovative ideas in Big Data.

10.- Thank you very much for your comments, what projects are you currently working?

I am founder of a company called DatoSphera using data to automate Big market research. My classes are inspired by the positive experiences in my company and also the mistakes I committed to work with data.