Data Analytics

No Luck Getting Data Analytics Job: Here’s Your Secret Sauce

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Business intelligence companies are increasingly hiring big data analytics trainers and certified analysts to speed up their processes and making information more actionable. As companies increase their IT budgets and hiring numbers, fresh graduates and professionals have a likely fertile job market. However, it’s not as easy as it looks or sounds, despite 150,000 job openings in the industry perennially available for the next 18 months or so.

If you have been on the wrong side of the job interviews and aren’t able to cut the mark with the companies you want to work with, here’s what you could try right now.

Get a Pulse of Data as a Service (DaaS) industry

70% of the job seekers looking for jobs after their graduation are completely unaware of the current trends in the Data industry. Between 2001 and 2018, the data industry has exploded exponentially, while the job market is growing at a linear scale. It has put intense pressure on the demand and supply equation in the Data as a Service capabilities for businesses that are continuously building and innovating with new capabilities.

Data analytics training that cover DaaS trends provide powerful coaching in data management and data analytics, focusing entirely on selling products, software and sourcing accurate information.

Augmented Intelligence: The Key Selling Point

Are you aware of Augmented Intelligence and how it’s different from Artificial Intelligence and the over-arching technologies that are driving the augmented intelligence adoption?

According to Gartner, a leading research organization, augmented intelligence and Augmented data management would be the top selling point for organizations that are catering to the BI and Data Analytics market.

In Augmented Intelligence solutions, you should be aware of these key selling points –

  • Augmented Data Management
  • Master Data Management
  • Metadata Management
  • Self-service DBMS and self-tuning

Breaking Barriers in Analytics: Quantum Computing

Given today’s Big Data evolution, Quantum Computing is a powerful trend that you should be prepared for. Quantum Computing trends reveal the sustained efforts of over 5 decades into developing mathematics, statistics, material science, hardware and software advancements, semiconductors and computing knowledge—all coming together under one shelter. Quantum Computing is applicable to all the basic disciplines of science and mathematics, and also to Quantum Search, Marketing and Sales Analytics, Data visualization and so on.

The Latest Entrant: Blockchain

Few months back, no data science exponent would have imagined that Blockchain would percolate into their core functions. A blockchain is essentially a distributed database of ledgers and digital events. Data management could use blockchain applications to standardize data interactions, especially when you have to deal with Big Data using traditional data processing methods.

Today’s data management challenges like security, data leakage, fraud analysis and encryption/data trustworthiness can be solved using the Blockchain.

Several businesses in the banking and finance, cyber security and social media are already leveraging Blockchain applications in their Data Analytics processes.

Foreseeable advantages of Blockchain applications in Data Analytics training –

  • Real-time data analytics
  • Seamless, platform-agnostic Data Sharing
  • Technology-agnostic pricing and product recommendations
  • Better Customer Data Management

Data Visualization, Graph Analysis and Voice

The super three – Visualization, graph analytics and conversational AI, are the next enabling factors for creating frictionless “flywheel” of customer experience. These technologies could be a core of every Data analytics program, providing enterprises with heightened capabilities of data management, relationship analysis, and graph database management using new stream of data mesh approaches.

By 2020, 50%-60% of the phone-base queries would be completely managed by voice and AI-based chat assistants. They could be a primary interface with the customers seeking inquiries that are generated via search, website chat messenger, social media messengers, email inquiries and phone calls. In 2022, Data analytics with Natural Language processing and Conversational AI science would help companies to build and leverage powerful bespoke data fabric architecture for better customer interactions and employee engagement.

Do You Know: Who is A Leader, Who’s a Challenger and Who is Lagging?

In the various market analysis reports, technology drivers are measured by analyzing the leaders, challengers and laggards in the business, ranked by virtue of their pace and ease of adoption of a technology.

The leaders and challengers are:

  • IBM
  • Google
  • Facebook
  • SAP
  • SAS Analytic
  • Adobe
  • Salesforce
  • Oracle
  • Twitter
  • Baidu

In Data Analytics training, every company in the Leader-Challenger quadrant should be your target to get a job or project.

With these helpful pointers, you should be able to get over the finishing line.

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