What is the Major Impact of Data Analytics in this Data- Driven World?

Data Analytics is one of the hottest professions in the world right now. According to a report by the McKinsey Global Institute, data and analytics present a wide range of opportunities for business, and as technologies surrounding big data perpetuate making advances, we can expect that the potential applications and opportunities of data and analytics will perpetuate growing. “Big data analytics sector in India is expected to witness eight-fold growth to reach $16 billion by 2025 from the current level of $2 billion, the National Association of Software and Services Companies (NASSCOM)”.

Where is Data Analytics found?

It comes from sensors, devices, video/audio, network, log files, transactional applications, web, and social media. A lot of data is generated in real-time and on a very large scale. The analysis of data allows analysts, researchers, and business users to make better and faster decisions using data that was previously inaccessible or unusable.

Utilizing Data Analytics for Better Decision Making:

Data is the new oil and the best way for companies to access and understand it is to digitize their processes. Data Analytics can help reduce costs, improve processes, improve existing products and services.

Here are some points, how data analytics to help organizations, stand out among top players:

• Remain competitive among forward-thinking companies that do utilize data to their advantage.
• Efficacious data collation, combined with analytics, avails companies stay competitive when demand changes or new technology is developed. It also avails them to anticipate market demands to provide the product before it is requested.
• Data Analytics reduces banking risks by identifying probable fraudulent customers predicated on historic data analysis. This avails banks in deciding whether to issue loans or credit cards to the applicants or not.
• Data Analytics is utilized by security agencies for surveillance and monitoring purposes based on information amassed by the huge number of sensors. This avails in obviating any wrongdoings and/or calamities.

How Top Firms are leveraging Data Analytics?

There are so many organizations, whose entire business models are cantered on Data Analytics, such as Flipkart, Amazon, Pinterest, Instagram, Uber, Ola, Spotify, Wal- Mart, Facebook, etc. Many more companies disrupted their respective industries and hold the greatest market share mainly because of their data and analytics assets.

E-commerce companies, such as Wal- Mart & Amazon are using data analytics for tracking browsing behavior of their customers, which help them to understand their customer choice and help them to display the products that specify the users will be more likely to order and purchase.

Banks, like Axis bank, is using SAS Data Analytics to improve risk management throughout the organizations and helps them to take the best possible business decisions. HDFC Bank uses SAS Data Integration and SAS Anti-Money Laundering (AML) to capture and organize customers’ activity. SAS Data Analytics helps them to integrate with the customer and speculate with a 360-degree view. It helps them to decide whether they should seek for overleveraging or under leveraging. It also helps them to know about the behavior of the customer while using their services. SAS tools are extensively used for market analytics and credit risk analytics in HDFC Bank.

Social Media giant, Facebook is Data Analytics to understand customer’s posts and recognize their face. With the help of data analytics, Facebook is deciding, which advertisements to show to which users.

Data Analytics help the manufacturing sector to understand customers' requirements, categories, and behavior. It helped them to understand their market share, the impact of competitor's activities, how to monitor their machines, and how to monitor their supply chain of the products, etc.

The Healthcare domain is utilizing Data Analytics to improve operational efficiency, advanced patient care, finding a cure for diseases, prediction of deadly diseases, reducing death rates, cost reduction, etc.