To say that Data Science will remain but Big Data will fade away is a paradoxical statement. But to clarify it, let’s first simply define Data Science and its necessity.
Data Science as the name suggests is a science; a study of data. It is the blended use of computer coding with statistical techniques and mathematics, to cleanse, prepare and analyze data, for deriving valid and vital information from large amounts of data that supports business purposes.
Big Data on the other hand is humongous amounts of data, which cannot be managed and analyzed using traditional tools and methods.
There is a third cog to this data machinery and that is Data Analytics, which comprises of techniques and tools to analyze data, big or small.
If Big Data needs to be analyzed, you as a Data Scientist would use Data Analytics to conduct the analysis.
Big Data is nothing but the purest form of data. Till we continue to have digital systems and the Internet, we will have Big Data in ever increasing quantity. Our dependence on Big Data will not just stay, but will increase exponentially as the quantum of data increases. To get a perspective to the quantum of data we are amassing, let’s look at a few statistics about data:
In the last 2 years, we have generated more data than all the data created since the advent of human.
By 2020, we would have creating information at the rate of 1.7 megabytes of new and unique data per second per person.
While today the total data size is estimated at 4.4 zetta bytes, it is anticipated that by 2020 it would have risen to 44 zetta bytes, or 44 trillion gigabytes.
The skeptical notion that Big Data is beginning to fade away is just an outcome of Big Data becoming commonplace and the hype around it is dying down. Today, every size of business generates, assimilates and analyses data that was not available to them just a few years ago.
Data, or Big Data, is not the big problem we face. It is our ability to analyze that data and extract conclusions that are relevant at the same pace at which we generate that data. Currently, we analyze only 0.5% of the total amount of data being generated and already we have insights into business improvement that were unheard of till now. Imagine what could be done if we are able to harness and process even 10% of the data assimilated.
There has been a paradigm shift since the appearance of Big Data in the way we use data today:
- We are able to analyze complete sets of information, rather than small subsets of it.
- Earlier, almost 80% of the time was attributed to managing the data while only 20% was spent on analyzing it.
- The old technique of analyzing data would start with a hypothesis that was tested on selected data. Now we have the capability to explore BigData to identify any correlations or anomalies that may exist.
- Today we can analyze data on the fly, even as it’s being generated.
Analysis of Big Data helps in improving customer experience. You are able to create a 360°perspective of the customer journey. Every customer interaction generates additional information. As data continues to be collected across multiple channels, it contributes to enhancing the customer profile and a clearer understanding of the customer needs.
Big data augments the existing data warehouses. Hadoop platforms are also used for used for landing zones to stage and prepare the data for existing data warehouse.It is used for expanded storage and long-time archival of detailed and historic data records.
Internet of Things is changing the world at breakneck speed. Every connected device, from mobile phones to sensors, RFID tags and smart meters continuously creates tremendous amounts of data. This is happening across every type of industry, be it transportation, manufacturing, automotive, energy utilities, healthcare or more.
Big Data is changing the way organizations analyze data and generate plan and strategies to increase sales, reduce cost or reduce churn, besides a host of other intrinsic business requirements. Companies that desire to be forerunners in this new digital and industrious age need to embrace and optimally use Big Data.
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