[br]Data analytics is transforming business operations and data analysts are leading the change. Several sectors, ranging from travel to the healthcare industry, are utilising analytics to optimise performance, and operations, and offer better service to their customers. Data analytics is a prospering career domain where the highest CTC could reach up to 24 LPA in India. Ideally, the data analytics definition involves extracting valuable patterns and trends from extensive sets of structured and unstructured data. A data analyst uses statistical techniques and advanced tools to optimise processes and identify growth opportunities.
According to a recent report, data-related roles, including data analysts, are projected to witness exponential growth over the coming years (Source: by the World Economic Forum). The report further highlighted that by 2025, over 85% of companies are expected to have embraced data analytics as a core component of their business strategies. These statistics underscore the supremacy of data analyst skills and training in the modern career domain. In other words, a career in data analytics is highly rewarding in the 21st century.
Undoubtedly, data is a valuable asset- but only in its filtered form. Each day companies generate tonnes of raw, unfiltered data. But organisations cannot extract much value from this tangled mess of information. This is where organisations need data analysts. It’s only when a data analyst cleans, sorts, and processes this information to arrive at valuable insights - the companies can reap the benefits.
Technically speaking, data analytics is a process of analysing raw, unfiltered data to uncover meaningful, actionable insights, which are then used for driving smart business decisions. In simple terms, data analytics helps solve specific business-related problems with the help of data. It helps uncover hidden patterns in a particular dataset to understand how a certain customer group behaves or track the overall productivity of the employees in a particular department.
With data analytics, organisations can understand upcoming trends and customer behaviours - resulting in more informed decisions and planning on the organisation’s part.
Data analytics and data science are the two most frequently used terms of the 21st century. Both domains intermingle with each other and share a fair amount of similarities and differences.
While
data science involves extracting valuable information, insights and patterns from vast and complex datasets, data analytics' primary concern is studying datasets to uncover trends and correlations to derive meaningful conclusions. To uncover hidden patterns and make predictions, a data scientist uses a combination of programming, mathematics, statistics, and machine learning techniques. However, a data analyst uses statistical analysis and visualisation to facilitate the decision-making process.
To understand data analytics and what data analysts do, let us go through this case study. Imagine a book-selling e-commerce website, WeRead.com, that has more than 10,000 registered customers. On an average day, the website has 15,000 new visitors which increases up to 25,000+ on special occasions like annual book sales, exclusive book launch events, or subscription box announcements.
WeRead.com is trying to improve the overall consumer experience, develop retail price optimization models, and introduce a weekly book recommendation email blast for its client base. The website has the billing data, payment method, purchase history, etc. of their clients.
To work through these aspects, a data analyst will use multiple tools and techniques to clean, sort, and transform raw data into a usable format. Then they will apply statistical methods and visualisation tools to identify hidden patterns and trends within the dataset. The process will be followed by detailed reports and presentations, based on thorough analysis. Once the report is ready, they will communicate their findings to other members of the team.
So far, you know that a data analyst uses multiple tools and techniques to work around data. Although you do not need to learn - everything, everywhere, all at once - to become a successful data professional, familiarity with most of the tools could be helpful in building a career in this domain.
Here are the Top Ones:
From Fortune 500 giants to budding startups, everyone is hiring skilled data professionals to process and analyse unfiltered, raw data for valuable insights. Here are some of the high-paying industries hiring data analysts:
Top Career Roles In Data Analytics Domain
The future of data analytics is a highly promising one. Advancements in technology, integration of AI, and increased focus on data privacy will shape how organisations use data. Simultaneously, with the rising emphasis on data-driven business operations, the domain of data analytics seems to offer a wealth of possibilities for aspiring professionals.
Data analysts are a major driver for a paradigm shift in the modern world. With technological advancements and the increasing availability of data, this field will grow exponentially building exciting opportunities. By staying up-to-date with the latest tools, and techniques, you too can position yourself in this dynamic and ever-evolving field.
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