We have less than a year to get through this decade and it is a good time to look at how things have fared in the field of analytics. This decade has without any doubts been the period that has shaped the field of big data analytics and data science. Some practices have become obsolete, some have retained their position. Overall analytics has dug a stronger foot in a variety of markets. It is a good time to join a big data analytics institute in Bangalore. But before that, let us point out some major shifts that characterize the flux in the analytics industry.
The advent of big data
The amount of data we collect and handle on a daily basis today was hardly fathomable ten years ago. Companies had started to realize the value of data but only the largest corporations could afford the hardware required for handling large amounts of data. So, as the time demanded we had big data tools and technologies. Distributed computing became the key to the problem of affordability. Hadoop came up with the Hadoop distributed file system or HDFS and the first step towards democratizing data analytics was taken. Now, be it in the data lakes or in the cloud, companies are making good use of their data regardless of their size and worth.
Embracing more speed
HDFS afforded a lot of storage space and processing power but the industry needed more speed precision. That is where Spark came into play. This tool took data analytics to a whole new level by introducing incredible speed through in memory data processing. Spark skills became relevant at that point and it still is greatly relevant for an aspiring data analytics professional. A skill set combining Spark and hadoop skills can really take you places.
Analytics on the edge
As if things were not fast enough, we were introduced to edge analytics or, as it is called, real time data analysis. This refers to the method of analysing data at its source. We all know how an air conditioning machine works, right? It switches the compressor on or off in order to maintain a certain temperature in the room. Real time analytics has a similar way of functioning. The system analyzes the data and instantly prompts an action.
This leads us to machine learning and AI
No discussion about analytics can end without referring to machine learning and eventually AI. These technologies could not have become what they are today without the presence of big data. Currently businesses across India are investing on machine learning with the hope of faster and more accurate insights from data.
Finally neural networks
Emulating the functionality of the human nervous system – this is how far AI technology has reached today. Thanks to the availability of immense amount of data and the computational prowess to deal with it. Deep learning with neural network has totally changed how machines are perceived in the real world. With language and speech recognition improving by the day we are not far from the future.