The last two decades alone have created 98 percent of all data that has been piled up since we started writing history. In 2010, Google's Eric Schmidt estimated that the world created around 5 exabytes of information between the dawn of civilization and 2003. Currently, there are 2.5 quintillion bytes of data created each day, and the pace is only going to accelerate with the onslaught of the Internet of Things (IoT) and other connected devices.
By 2025, it is predicted that global data production will reach 463 exabytes per day. Data-related occupations are expected to grow over 31 percent by 2030. Hence, the role of big data professionals armed with computer programming, statistical, and mathematical knowledge is fundamental to supporting the teams to formulate plans and strategies. We need Big Data experts to ensure that data integration pipelines are improved, supply chains can be sharpened, and more collaborative environments are created.
Whether it’s equipping the meteorology departments for more accurate and real-time predictions on climate change, and earthquakes, or diffusing pandemics, Data Science professionals can do it all.
Data Science has branched off into multiple specialized tracks in the last decade to help global data factories rebuild themselves into producers of Business Intelligence for corporations, government agencies, and other organizations. Though all Data Science professionals or specialization tracks still retain their traditional foundations, the methods and tools used to manage big data have changed dramatically – as the scale, complexity, volume, velocity, and variety of data keep exploding through the roof – both confounding and exciting decision-makers at the same time.
The transformation of data into Big Data has not only added to the complexity of conventional data jobs, but has also generated new categories of interdisciplinary roles and spawned an era of Data Science career tracks – many of which demand multi-dimensional competence.
Data Scientists blend their knowledge, experience, and insights on business, marketing, specialist subjects, and management with their expertise in research and statistics to explore, define, and innovate ways through which data can be used by organizations to make more accurate, meaningful, and real-time decisions.
They also architect the analytics ecosystem required to convert petabytes of Big Data into solid chunks of Business Intelligence for corporations and governments.
Big Data Analysts model and analyze huge chunks of data in sync with their objectives by using their skills in mining, researching, and analyzing data on specialized statistical and mathematical analytics tools.
They deploy their knowledge and understanding of business and management fundamentals to generate insights from their analysis.
Big Data Developers/Engineers design, code, program, and build specialized software applications used in handling and managing Big Data.
They use their skills in programming and software testing to work on popular Big Data platforms such as Hadoop and Spark and also have knowledge about domain and analytics tools and techniques.
Big Data Architects do all the essential planning and coordinate data resources in an organization. Knowing about application architecture acts as a plus point to advancing the career of a Data Architect.
They combine their experience, skills, and expert knowledge about data systems with their exposure to data management processes and data analytics to help build the infrastructure required to cluster, segregate, distribute, mobilize, and transfer Big Data among various stakeholders.
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