It is quite fascinating how earlier in the age of analytics adoption data storage was a huge issue. Businesses were spending fortunes merely to hold the data that was being created. Things changed completely within a few years after the advent of Hadoop distributed file system or HDFS. With tools for data storage and processing Hadoop software suit had come to be synonymous with big data.
Now, we have almost real time data processing thanks to Apache Spark. We have machine learning algorithms to analyze data with more speed and accuracy. We have AI based analytical engines that can create real time alerts by recognizing data. The point is that the field of analytics is in a constant mode of flux. So, it is important sometimes to look at the developments from a distance to decide upon a course of action as a professional.
Stress on real time analytics
In the initial years of big data analytics companies built data lakes to store data and process it. A lot of questions are being asked about the functionality of data lakes in today’s scenario. Experts are putting a lot of stress on real time data analytics. This means analyzing and acting upon the data as it is generated.
A simple example can state how this makes a huge difference. Suppose there is a surveillance camera at a remote cross-road. The camera records an accident in the middle of the night and the footage is stored in a database to be discovered on the next morning. With real time analytics the footage of the accident could be processed and understood instantly. It could have raised an alarm or alerted a state official to tend to the victims.
Companies today are not ready to lose the moment; hence the importance of real time analytics is increasing. A big data online course may be in order to help you update your skills.
Machine learning has more takers
When we are talking about real time image processing or language processing we cannot but mention the role played by machine learning in all of this. It is through machine learning that a software learns to discern the implications of an image or a word. Companies across the world are looking to find faster and more accurate ways of analyzing big data as a result machine learning professionals have become the need of the hour.
GDPR is asking a question or two
General data protection regulation or GDPR is the recent step taken by the European Union to ensure better protection of information. This is forcing data driven companies to rethink their ways of accessing and using data generated by the users. The situation gives more importance to the role of CDO or chief data officer who can make sure that a company is free of data related encumbrances.
Time for setting goals
A lot of companies have supposedly lost some money due to poorly directed data analytics ventures. This is time that companies set their analytics goals well and work on well targeted areas in a well planned manner. The data needs to be sorted for distinct purposes before being analyzed. The data curator working between the data miners and the analysts are sure to find more prominence now.
It is better to keep yourself updated with information as well as skills. Big data online courses can help you up-skill without changing your professional schedule too much. There is probably some new trend in the making right now and you do not want to be left behind.