Article: Skills needed to be relevant in the Big Data industry

Skilling

Skills needed to be relevant in the Big Data industry

To keep up with the fast-moving pace of analytics and changing technology landscape, one must be aware that certain tools and skillsets might be necessary in order to avoid from being redundant or obsolete.
Skills needed to be relevant in the Big Data industry

In the coming year, Big Data technology will continue to be the big thing for business. Experts estimate the amount of data some companies hold could be worth $8 trillion or more. Access to such a massive amount of data can be both a curse and a blessing. It can help reduce decision-making times on one hand; and on the other hand, it also increases the need to hire right people with the right skill set to draw meaningful insights from this data.

Evolving complexity in the Business Ecosystem and how companies reach out to their respective audience (consumers/clients) brings about the need to innovate and enhance skills. Conventional Analytics programs and basic level modeling analysis will not suffice. Big data analytics involves complex, yet simplified user interface software tools applying predictive analytics and data mining. Hence, the new form of big data technologies, such as NoSQL and Hadoop are used in many different analytics environments. Big data analytics is making an extreme case for business and software evolution with related skill-sets – these have to constantly evolve with time. Those who do not adapt and evolve with it will surely and suddenly disappear.

To keep up with the fast-moving pace of analytics and changing technology landscape, one must be aware that certain tools and skillsets might be necessary in order to avoid from being redundant or obsolete. Listed below are some skills and tools which one should know:

Knowledge of Hadoop: It is the poster child for Big Data, so much so that the open source data platform has become practically synonymous with the wildly popular term for storing and analyzing huge sets of information. The year 2017 envision a surging growth in demand for big data professionals with Hadoop skills in India, the year also senses an increased temptation of excellent job prospects for professionals with big data skills in the analytics sector. Currently India is viewed as the most loved outsourcing destination for Hadoop skills, attributed to its highly talented IT experts, operational efficiencies and low cost

Cloud and distributed computing: Companies have now started preferring distributed computing, which enables multiple computers to network with one another to solve a task. Many of the skills involved with cloud computing and distributed computing are related, so the two are often grouped together. Skills to learn include SQL for database management, programming languages like Ruby, JavaScript, and Python for building cloud-based applications, and DevOps (a software development system popular in the cloud computing field). Specific in-demand programs include Microsoft Azure and Amazon Web Services

Other Important Analytics Skills: Data scientists should improve their understanding on the following skillset and it will definitely give them competitive edge in 2017.

  • Apache Hadoop
  • Apache Spark
  • NoSQL
  • Machine Learning and Data Mining
  • Statistical and Quantitative Analysis
  • Data Visualization


In the coming days, a good Big Data scientist must possess strong mathematical and analytical skills along with equal proficiency in handling massive data sets. One must be able to crunch numbers, understand the math behind building models, and find useable insights. To communicate the data findings effectively, data scientists also need sound knowledge of the business domain and an understanding of customers and processes. Managers at all levels need knowledge, skills, and experience to effectively start a career in this industry. In a nutshell, it is imperative to have the following right set of skills — including coding, statistics, machine learning, database management, visualization techniques, and industry-specific knowledge in order to be ready for the changing technology landscape.

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Topics: Skilling, Technology

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