“I never guess. It is a capital mistake to theorize before one has data. Insensibly one begins to twist facts to suit theories, instead of theories to suit facts.” -Sir Arthur Conan Doyle, Author of Sherlock Holmes stories.
The revolution of rapid increase in data over the cloud, has laid a path to data analytics. Data analytics is said to be a predictive analytics of data. To describe the main features of data sets to support the business operations and decision making. Here, the data analyst gains information through research and by extracting information from various sources. Vendors are making the analytics tools easier to use, with the right controls in place.
Importance of Data Analytics in the Organization
At present, data analytics has become a lifeline for the IT industry which shares data that’s important to the customer. Together, they use that data to gain an advantage and be successful in the marketplace. Many have already heard of techniques such as big data, data science, machine learning, and deep learning over a lot of times which are used in analyzing vast volumes of data, and are expanding rapidly. In order to refine data analytics strategy and to be a successful data scientist, one needs to gain deep insights of customer behavior and system performance.
The organization collects data gathered from customers, businesses, economy and practical experience. Then the data is processed and is categorized as per the requirement and analysis is done to study purchase patterns etc.
Top Trends of Analytics in various Fields
Health care Industry
Currently, wearable devices can be used to detect the patient’s sleep, heart rate, exercise; distance walked and provides data to the humans. Along with the sensor data collection which will allow healthcare organizations to keep people out of the hospital. They can also identify the potential health issue and provide care. Through this, healthcare industry is going to utilize analytics in a bigger way to gain information by continuous monitoring of the body vitals. Data analytics can be leveraged to analyze user data and the prescribed medication to reduce mistakes and save live. It will not only be able to provide accurate solutions, but also offers customized solutions for unique problems.
Insurance Sector
Insurance is an inherently data-driven industry to prevent and reduce fraud and wastage. The data analytics is acting as the game changer and is being used to figure out who is most likely to commit insurance fraud before it ever happens. The data can be monitored in real-time from various social media platforms to see if a policyholder might be engaging in fraud.
Predictive analysis will reduce the rate of investment incurred by hospitals. Further, by backing wearable’s and health trackers to ensure that patients do not spend time in the hospital which saves money for insurance industry. It can also save the waiting time of patients since the hospital will have adequate staff and beds available as per the analysis all the time.
Retailing Solution
“The ability to capture end to end customer information is the biggest challenge for a retailer. The ability to merge structured and unstructured data into an Analytics Platform and be able to generate cohorts effectively is a challenge in today’s landscape. There is sudden surge of data and ability to manage the same and generate meaning out of the same is a challenge.”-Piyush Kumar Chowhan a VP & CIO of Arvind Lifestyle Brands.
Over the years, lot of operational changes has been experienced by retail industry and data analytics solutions is playing a critical role in helping retailers to bring those changes. Since, the adoption of analytics solutions is growing steadily with more retailers and working incessantly towards enhancing supply chain operations. Also, by improving marketing campaigns, and increasing customer satisfaction and retention to achieve high levels of retail success.
The Next Generation of Analytics in the Market
A set of collected data is used to follow the path, and those data points gives information about what’s happening, where it’s going, what can be used to predict the outcome. Then understand the conditions and context to which some of those things happened, and how can it be changed to get positive outcomes.
In the next generation of analytics, data analytics will be playing a crucial role on internet of things, hyper personalization, artificial intelligence, machine intelligence, augmented reality. Also on behavioral analytics, graph analytics, journey sciences, the experience economy, agile data science to transform the marketplace a better place for the organizations and customers too.