Big data challenges

These days big data is something that every company has to deal with. When it comes to big data, the most important challenge was how to split data into pieces, such that we could run and implement each piece on various models.

I think Hadoop is a good choice to tackle with big data, in fact it is useful in many companies. The question is how we can make our raw data to understandable data for these kind of tools? Hadoop is an open source software which does the parallel learning and combining procedures.

In fact changing the raw data to something meaningful is currently a big issue for most companies especially in terms of time, as machine learning systems need the data to be in row and columns format. there is another name for this which is prep process.

Sometimes there is need to perform thousand of steps to prepare the data for analyzing. Recently ALFA made a some breakthroughs in this area which makes the subject totally interesting to follow for machine learners. You may find it quiet interesting as well!They reduced the time of prep processing as well as making the process automated.

The most amazing part of this area is the existence of a decision making among the progress, which means people can be used in order to predict.