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Career Opportunities in Big Data Analytics

Data analytics provides organizations with key insights that are useful in tackling complex problems. Successful organizations do not like to sit on decisions and waste good opportunities. They like to stay ahead of the game and gain the first mover’s advantage whenever and wherever possible. Therefore, data analytics has become an indispensable part of their operations.

Most big organizations already have a sizable department looking at data to gain critical insights. Those catching up are still expanding this department to increase their data analytical potential. It is safe to say that in this environment, data analysts are prime assets. In this article, we look at the prospects for a data analyst. First up, some predictions pertaining to big data analytics:

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Predictions for Big Data Analytics

According to tech billionaire, Michael Dell, big data analytics is the next trillion-dollar market. The International Institute for Analytics (IIA), Forrester, IDC, and Gartner have also made positive forecasts for the field. Let’s look at some of the predictions:

  • The market for Big Data technology and services will grow at a 23.1% CAGR, reaching $48.6 billion in 2019. (IDC)

  • By 2020, big data analytics will be everywhere. 50% of all business analytics software will include prescriptive analytics. (IDC)

  • Automated data curation and management will free up analysts and data scientists to do more of the work they want to do. (IIA)

  • Machine learning will replace manual data wrangling and data governance. (Forrester)

  • Machine learning solutions will take control of ingesting, preparing, and discovering data. (Forrester)

  • And lastly, by 2020, the spending on data preparation tools will grow 2.5 x faster than traditional IT-controlled tools. (IDC)

Type of Analytics

There are broadly four categories that big data analytics presently falls under. These categories are determined by the environment in which big data is used. The categories are as follows:

  • Prescriptive Analytics

  • Predictive Analytics

  • Descriptive Analytics

  • Diagnostic Analytics

Prescriptive Analytics

Prescriptive analytics is a subset of business analytics. It aims to suggest the best course of action for any given situation. The analysis usually is both descriptive and predictive. Therefore, it explains the situation in detail, lists possible solutions, along with their implications to help decide the course of action. 

Predictive Analytics

Predictive analytics is a branch of data mining. It predicts trends and future probabilities according to inputs or the set of data.  Predictive modeling is an important process in this kind of analytics. It uses new and old data to either validate or alter its predictions. Decision analysis, optimization, and transaction profiling are key processes in predictive analytics.

Descriptive Analytics

Descriptive analytics is the initial stage of data processing that creates a summary of historical data and prepares the data for further analysis. Data aggregation and data mining are used to organize the data and identify patterns and relationships. Querying, reporting, and data visualization are other ways of gaining more insights.

Diagnostic Analytics

Diagnostic analytics looks at data with the intention to understand the cause of events or behaviors.

Career Opportunities in Data Analytics

Data analysts are progressing well in the field of data science. According to itjobswatch, the demand for analytical skills is on the rise. A study by RJMetrics on LinkedIn profiles have also yielded the following insights:

  • High-tech industries like the IT or software industries employ 44.9% of the data science professionals. Academia employs 8.3%, banking and financial sector employs 7.2%, and marketing and advertising sectors employ 5.2% of data science professionals.

  • Top ten companies employing data scientists are Microsoft, Facebook, IBM, GlaxoSmithKline, Booz Allen Hamilton, Nielsen, GE, Apple, LinkedIn, and Teradata.

  • Most sought-after data analysts are proficient in R, Python, machine learning, statistics, SQL, MATLAB, Java, statistical modeling, and C++.

  • Predictive analytics professionals continue to remain in high demand due to the shortage of professionals with good analytical skills.

Pay Package for Analytics Skills

According to Indeed, a popular job portal, the average salary of big data professionals is $ 110,000 per annum. Itjobswatch, a U.K-based job portal, quotes the average salary in big data analytics to be 65,000 GBP per annum. The average salary in both these nations are close, and both countries pay their big data professionals well.

IT recruiters, as well as companies, agree that data scientists are hard to find. Hence, they are willing to pay more. Some data scientists make well over $ 200,000 per annum. A study by O’Reilly states that data scientists can make more than $240,000 annually. Numerous surveys confirm that the increase in implementation of data science is increasing remuneration for other data analytics professionals as well. 

Burtch Works’ study on the salaries of predictive analytics professionals reveals that predictive analysts continue to benefit from the increasing demand for and short supply of analytical skills in the market. According to their report, the median base salary falls between $ 76,000 (for professionals with 0 to 3 years of experience) and $ 125,000 USD (for those with 9+ years of experience).

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Job Titles Given to a Data Analyst

Here are some of the job titles that are given to data analysts:

  • Analytics Engineer
  • Big Data Scientist
  • Data Integration Lead Architect
  • Big Data System Administrator
  • Data Scientist
  • Big Data Architect
  • Big Data Engineer
  • Data Analytics Architect
  • Big Data Analyst
  • Business Intelligence Architect
  • Solutions Architect

Companies Hiring Data Analysts

Although most organizations are actively looking for good data analysts, here’s a list of prominent organizations that are always looking to benefit from the advantage that data analysts can provide them.

  • IBM
  • Pearson
  • Verizon
  • JPMorgan Chase
  • Honeywell
  • AT&T
  • Wells Fargo
  • Booz Allen Hamilton
  • United Health Group
  • Ebay
  • Uber
  • Deloitte
  • Shutterstock
  • Fidelity Investments

Conclusion:

This is a good time to gain skills in data analytics as per market predictions and job trends. The growth is expected to sustain itself, if not grow further, as more  companies look to make the best use of real or live data. Add to that, the shortage of professionals with good analytical skills, and you’re setting yourself up for a thriving career. Make the best of this opportunity by learning data analytics. Subscribe to our blog for updates on big data and related technologies. Click here to learn Big Data Hadoop  and Spark Development.

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