Winning or Losing: How data analysts are faring in the industry?

Data Analysis — it is a startling industry to work in. In less than 10 years, the entire ecosystem and the components that govern the landscape have completely changed. Today, the business analysts are largely coming from the league of top data analytics courses that train engineers and software programmers in various fields of data science, automation, and machine level algorithm designs. If you are looking for a passionate entry into the fastest growing technology stream, this is a chance to make it big. But, have you really done the groundwork on what it takes to be a top data analyst and if the ones that are already part of the industry are really doing well? So, if you take the last 5 years of the data analysis industry, few things have been game changers in the way this job role has evolved to give rise to a talent war among top organizations. Data scientists, AI engineers, big data architects, automation developers and a horde of other multi-faceted job titles have emerged to show what the data analytics market is all about. In this article, we will evaluate the growth trends of these professionals working in various domains or segments within data science, and what the future holds for them.

Business data operations 

Data organization is a real thing. From paperwork to 100% paperless organization, businesses have understood the magic data bring to the enterprise. What began as a journey towards becoming a digitized business unit has now emerged as the single biggest cost saving and productivity enhancer. Data organizations, that use and provide data as a service, are ruling the roost in the industry. Every company is trying to find newer ways to assimilate data into their existing processes and refine these systems to develop new lines of products, services, and associations. Considering the fact that the Cloud is pivoted at the center of this digitization journey, data as a service is the biggest job market for data analysts who are trained to handle big data analytics, business analytics, and a plethora of other data science related operations that make organizations “more powerful” with data.

Data governance 

Data analysts are not just operations managers. They have become the “data stewards”. This is a very popular term used by professionals working in the IT data management teams. The number of stewards of data is constantly rising, and so are their compensation packages.

Business integrity has moved from enterprise finance to IT systems. Today, a bulk of the investments is happening in data governance which has become the core of financial health and business compactness. Leaders are tying the loose ends that left data on the table – whether it was business data, customer data, or financial data. Top analysts are hired from the best data analytics courses to handle data governance to ensure internal and external standards are fully complied with for effective data management in a trustworthy manner. Data analysts are definitely lagging a bit, but not by much, when it comes to putting data governance as a business critical mission.

Making AI better

AI is an attractive domain, but a challenging one too. Not many data analysts fully understand the nuances of AI ethics and biases. Therefore, top level experts are now working in AI ML domains to specifically train data analysts in building a smarter, scalable ecosystem of Artificial and Augmented intelligence. These could deeply impact the ways businesses use and promote AI as part of their services and product lines. In order to make AI better, everyone from the coding world and data science world has to meet in the middle and ensure all operations are conducted within the framework of high level data compliance, ethics, and governance in a bias-free manner. These could mean developing supervised machine learning platforms that can offset the need to have human managers. This also means giving more power to the big data and analytics management teams to come up with newer ways of using predictive intelligence.

As the market continues to grow into newer regions, big data analysts and computing professionals have a solid road map ahead to nurture newer skills for the specialized domains. These would mean acquiring the skills necessary to deploy data analysis in Quantum computing. Edge/ Fog, Blockchain, the IoT sensors data management, and so on. The future trends would continue to favor the data analysts, and the market would remain competitive for self driven professionals.