The world of technology has exponentially increased its pace towards collecting a large chunk of data as the consumer behavior has changed since years with the boom of Internet. With the businesses being shifted to online platform, the data comes in streams through user interaction and clicks. Here is where the role of Data analytics comes into action.
Data Analytics involves the process through which a huge amount of raw data is processed and analysed to find trends and insightful learning for boosting business and profit. Data Analytics also helps in creating reports by finding gaps in the funnels of a business and thus, improving the source of diagnosed problem.
Let’s take an example of Netflix, an OTT media-services provider based in America. The customer acquisition is done through either website or app. The funnel comprises of the Free Trial where the potential customer gets the hang of the service, which might further lead the customer to buy the subscription pack. The next in the journey includes retention of the customers by engaging them on the platform so they are interested in renewing the packs. Data Analytics helps in the assortment of customer data and looking for how to make it a better experience for user. This includes the performance of app, tech gaps, sales gaps, etc. that helps in a profit-driven business eventually.
Analytics defines the data-centric approach and the future of technology lies within it. Firms relying on the data analytics are observed to be more agile in catering to the customer demands. The prime example of Jio will help you understand the significance of data in building a strong business. Jio build a platform to provide free communication and Internet around the world, which was a force of attraction for a lot of customers. This helped them in assembling an enormous amount of data of different kinds of users to engage and monetize them for other platforms they were simultaneously structuring, like Jio Fiber, LYF smartphones, Jio Net Wi-Fi, Jio Saavn, etc. Online services like Google and Facebook also manage the colossal amount of data through Analytics and to keep the customers engaged.
What are some skills required to become a Data Analyst?
· Programming skills are must
An optimum knowledge of programming languages like R and Python is essential to grow your career in Data Analytics. R compiles and runs on several platforms such as UNIX, Windows, and Mac OS. Python offers various Machine Learning and visualization libraries such as Scikit-learn, TensorFlow, Matplotlib, Pandas, etc.
· Knowledge of Statistics and Mathematics comes in handy
Descriptive and inferential statistics and experimental designs are important to know in order to become a Data Analyst. Statistics as well as machine learning techniques are used to analyse the data using Big Data that creates statistical models. This helps in the optimization of trends/patterns in the data.
· Data wrangling skills are convenient
The ability to process raw data and alter it into another arrangement, thus allowing a suitable method of giving a new structure to ease data analyzing, also helps in a profit-driven business.
· Communication and Data Visualization skills are cherry on the top
Data Visualization becomes a necessary skill to perform a data presentation and this further helps you to articulate the insights to the executives and managers of the company.
Data analyst works as a nexus of Information Technology, statistics and business that helps firms and organizations to grow and progress as a successful entity. The fundamental role of using data analytics for businesses is to enhance the service efficiency for customers and improve customer acquisition by working & analyzing on the collected data by resolving the detected gaps in various departments. Data Analytics includes the application of algorithmic or mechanical processes to create insights by searching for significant associations that builds a pattern along the data.
Coding Blocks comes as a savior as it offers various courses to reinforce your Analytic skills, like Machine Learning and Data Science, along with Python language. So, check out the courses with industry-aligned content right away to find a new ray of hope towards success and to become a future Data Analyst.
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