Top Big Data Skills for getting Big Data Jobs

Big Data is a collection of complex and large data sets such that it’s difficult to capture, process, store, search and analyze using a conventional database system which is offering more qualitative insights into our everyday life.

Big Data Technology is a software tool used for examining, processing, and interpreting the vast, sophisticated, structured, and unstructured data that is out of the processing capability of a manual or traditional data processing system. This technology helps in avoiding future risks by forecasting and conclusion formation. The knowledge of Big Data opens the door to several fantastic job vacancies in the USA.

Big data technologies can be analytical and operational. While analytical technique deals with the analyses of weather, stock market, etc., operational technology processes data related to daily activities like social media interactions, online transactions, etc. The possible domains of big data technology are mining, data analytics, data storage, and visualization. Below is a list of some majorly in-demand big data skills for grabbing the greatest job vacancies in the field of Big data:

Statistics

It is the foundation of Data Analytics. It is the science of collecting, analyzing, and making an inference from data, you’ll need it the most.

Generating data insights for Problem-Solving

It is the art of generating insights from that data. You must develop a Problem-solving mind. It will help you analyze and solve problems more easily.

Programming language

You need to start with a programming language in order to implement what you’ve learned theoretically like python programming.

Hadoop

Hadoop is a java-based open-source framework developed by Apache Software Foundation in 2011. This map-reduce architecture based technology supports a distributed data processing environment for the storage and processing of data. It analyses and stores data of several different machines at comparatively lower cost and higher speed.

NoSQL Databases

Immense popularity is enjoyed by traditional SQL as a relational database management system for querying, manipulating, and managing large and structured data. For handling unstructured data, NoSQL is used. In this database, data is stored with no particular schema, and each row is allowed to have its own set of columns. The larger grows the data; the better gets the performance of NoSQL. Some of the most commonly used NoSQL databases are Redis, Cassandra, and MongoDB.

Apache Spark

Apache Spark processes massive data using Scala, Java, or Python at a hundred times the faster speed as compared to the standard engine of Hadoop – MapReduce. A few components of Apache Spark are:

  • Spark SQL: used for creating datasets and data frames on top of Resilient Distributed Datasets (RDDs)
  • Spark Streaming: used for handling and processing real-time streaming data
  • Spark MLlib: used for performing Machine Learning
  • GraphX: used for graphs and graph-parallel computation

Presto

Presto is a query engine that is used to run interactive queries against all size ranging data sources. This java-based open-source engine allows queries on the data stored in Proprietary Data Stores, Relational Databases, Cassandra, and Hive. Apache founded Presto is not MapReduce dependent and makes data retrieval quicker. Checkr, Netflix, Repro, Airbnb, and Facebook are some of the renowned companies which are using the Presto tool.

Blockchain

Blockchain is a high-security rendering technology mainly used for safe payments and speedily transactions. This technology brings down the possibilities of fraud in sensitive industries by enhancing their transaction security. Some significant tasks in a business network environment that can be achieved through Blockchain are:

  • Privacy: can be used to ensure transaction security, proper authentication, and verification.
  • Smart Contract: can be used to include business terms in the transaction database.
  • Consensus: can be used to ensure agreement of all the business parties to network verified transactions.

Major Companies in the field of Big-Data

The major companies who are working in the field of big-data and data analytics having offices in all major locations in the USA are:

  • IBM is headquartered in Armonk, New York
  • Salesforce is headquartered in San Francisco
  • Alteryx is headquartered in California
  • Cloudera is headquartered in Palo Alto, CA
  • Crunchbase is headquartered in San Francisco, CA
  • Google is headquartered in Mountain View, CA
  • Oracle is headquartered in Redwood City, California.
  • Vmware is headquartered in Palo Alto, CA
  • Databricks is headquartered in San Francisco, CA
  • Cognizant, Plano, TX
  • Cognizant, Austin, TX
  • Tiger Analytics, Dallas, TX
  • Nigel Frank, Houston, TX
  • EY, Austin, TX
  • Apple, Austin, TX
  • PwC, Dallas, TX
  • HMS, Irving, TX
  • Visa, Austin, TX
  • JPMorgan Chase & Co., Plano, TX
  • JCPenney, Plano, TX
  • Amazon, Dallas, TX
  • General Motors, Austin, TX
  • Siemens, Austin, TX
  • Accenture, Dallas, TX
  • Cloudflare, Inc., Austin, TX
  • DELL, Austin, TX
  • AT&T, Plano, TX
  • HAN IT Staffing, Dallas, TX
  • Impetus, Rochelle, TX
  • Systel, Inc., Dallas, TX
  • iSphere, Houston, TX

Major industries where it has been really helpful

  • Healthcare
  • Economic Development
  • Understanding and Predicting Crime
  • Waste Management
  • Urban Transport
  • Retail
  • Social Media Trend
  • E-Commerce

Job Roles for Big Data

It is a broad field with plentiful job opportunities. There are several job roles for which you can aim for, that includes,

  • Business Analyst
  • Data Analyst
  • Statistician
  • Data Scientist
  • Data Engineer/ Architect
  • Machine Learning Engineer

Veriipro is a career website that brings potential job seekers and recruiters together. From fresher to experienced, this career website contains a massive collection of job vacancies for Data Analytics professionals in the USA.

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