Growth of Data Analytics in the Coming Years

The global big data analytics market size was tagged at $193 billion in 2019 and is set to grow at 10.9% over 2020-2027. Within this, India’s market share is about $2.71 billion and the rate of growth of data analytics trumps even the global market: 33% CAGR. Bigger the industry, more opportunities, better jobs and higher pay. The stage couldn’t be better set than this for you to launch a data analytics career.

analytics

Growth of Data Analytics

Just a decade ago, internet penetration was sporadic. Today, there’s hardly anyone who does not have a smartphone, and people usually own multiple other devices too. They are using these devices not just to make phone calls or send messages but for a wide range of activities like online shopping, mobile banking, even working from home.

While using data networks to buy a shirt, get a home loan or to execute a business project in another country, large volumes of data are generated, which is fast becoming a company’s biggest 21st century asset.

Data analytics is the field of processing and analysing this data to reveal patterns and insights that can help make better decisions — businesses can use it to serve their customers better, governments can use it to device better policies, and even individuals can use it to optimise their habits.

Data analytics has become so important to the business world that there is a separate domain called business analytics that focuses on equipping non-computer science professionals (marketing managers, supply chain coordinators, operations heads etc.) with the ability to use data to drive everyday decisions.

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How Does it Work?

A data analyst uses four main analytics methods in their everyday work:

  • Descriptive analytics: This creates a historical summary of the data.
  • Diagnostic analytics: This looks for the reasons behind events and behaviours.
  • Predictive analytics: This makes business forecasts based on existing data.
  • Prescriptive analytics: This suggests corrective actions based on the analytics data.

Data analytics skills in data cleaning and mining, interpretation and visualisation are the essential tools that an analyst will need to tackle big data analytics by solutions.

Rise of Data Analytics: Why is it Growing?

The analytics field has still not reached its full potential, mostly due to the rampant unavailability of good quality data. We believe that this will resolve itself in the next few years, and more data analytics will use their time to solve real-world problems than to clean and prepare the data.

When that happens, data analytics will deliver far more value than it is today. This will happen mainly in the following three areas.

Better Decision-making

As devices become more connected due to IoT, businesses are looking to get a better view of their impact in customers’ lives. Data analysts will be key to drawing the connections between unrelated datasets and explaining how they should be considered while making a decision.

Improving Operational Efficiency

Data analytics can identify invisible leaks and inefficiencies in supply chains, delivery processes, inventory planning etc. These are expenses that businesses can easily minimise to improve overall profit.

Analytics also helps to trace the effect of one department’s inefficiency on another, for example, over manufacturing by the production department can lead to storage challenges for those involved in warehouse operations. Analytics can help to predict period-wise customer demand to enable data-driven operations.

Delightful Customer Experience

Data analysts can break complex data down to what it means for the individual consumer. This helps to personalise products and makes sure that a customer is getting the best value front their interaction with the company. It also helps to optimise the complete customer experience, from brand awareness to customer retention.

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Growth of Data Analytics: How to Start a Career?

#1 Comfort with Tools and Techniques

Database manipulation through SQL, statistical programming with R or Python and data visualisation through Tableau or Power BI etc. are the core data analytics skills that you need.

Depending on your role, you may be processing invoices, purchase history, transactions, customer behaviour, web analytics data, viewership data, contracts, tables, graphs to images and audio and so on. These data analytics tools will help you do your work faster and more efficiently.

#2 Practical Experience

Knowing the tools isn’t the same as doing the job. Employers are looking for candidates who have the experience of using these tools to deliver business outcomes. This can only be demonstrated by a detailed data analytics portfolio of projects.

#3 Business Acumen

A data analyst who understands how data insights will benefit the business will be able to ask better questions, and drive more useful patterns. Data analytics growth in 2020 has seen analytics professionals join hands with business leaders, to combine both sales and tech to drive business value.

In fact, big data teams are no longer experimental projects on the sidelines. Ericsson calls data analytics and data science roles as ‘business-critical’.

#4 Career Strategy

While jobs and opportunities are aplenty, the data analytics industry is also very competitive. This means that your CV and portfolio alone may be enough to get you that dream job. To land the right job, you need to know where to look for jobs, how to answer interview questions, how to negotiate salary etc.

While you can certainly learn data analytics on your own, a good data analytics course will accelerate your journey.

It will give you a combination of practical inputs and theoretical knowledge that you can immediately use for industrial applications. You can even do this without a college degree: there are certificate courses, especially bootcamps that make you industry-ready in a matter of months. This is important as the end goal of a data analytics course must be for you to launch a career in analytics.