Three types of Analytics
More than trillions of GB data is being processed every second, companies are turning to analytics solutions to process a huge volume of data to extract useful information and improve decision making. Raw data is often storage of unstructured information. Data analytics is the invention, interpretation and discovery of useful data. Analytics relies on the simultaneous use of computer programming, statistics and operation research to elaborate useful data. Read more about What are the 3 primary types of analytics?
Data Analytics focusses mainly on two questions- Why it happened and what will happen next. data analytics is a multidisciplinary field which uses computer skills, mathematical modelling and statistics to gain valuable knowledge from data while assessing data. Data Analyst converts these raw data to statistically significant information. And this is where data analytics come into play. Data-driven plays a very important role in helping businesses to grow their revenue.
Data Analytics is classified into three distinct types. They are:
- Descriptive Analysis
- Predictive Analysis
- Prescriptive Analysis
Descriptive analytics uses data mining and data aggregation to provide a deep view into the past. Descriptive analytics tells about What has happened in the past. Descriptive analytics collect old raw data and convert it into an easy form that can be easily understood by humans. These types of data are useful to derive strong pattern and strategies so that it can be useful in future. Descriptive analytics uses a vast application of statistics (mean, median, mode, regression, correlation, averages, standard deviation).
Descriptive analytics is the first and most frequently used analytics in almost every business. It reveals crucial information about any business. Common applications of descriptive analytics are reports that provide historical information such as company’s production, financial reports, operations, sales and inventory. Descriptive analytics is basically the management reports which provides information regarding sales, marketing strategy, customer behaviour, operations, finance and relations among the various variables.
Use Descriptive Analytics when you need to understand at an aggregate level what is going on in your company, and when you want to summarise and describe different aspects of your business.
Predictive analytics is an application of statistics which deals with extracting information from raw data and use it to predict the trends and behaviour patterns. Predictive analytics calculates statistical probabilities of future events online. Predictive analytics uses statical techniques which includes data modelling, data mining, deep learning and AI deep learning. Predictive analytics can be applied to predict past, present and future. Predictive Analytics uses theorem and applications of Probability theorem to predict what might happen in future.
Predictive Analytics estimates about the likelihood of a future overcome. Although it is impossible to predict the future with 100?curacy, Predictive analytics display a clear image of future outcome with less error.
Predictive analytics try to take the data you have and fill the missing data with best guesses using different outcomes. They combine historical data found in CPM, ERM, POS, HR systems to identify these patterns in the data and apply statistical data and algorithms to find relationships between different data sets. predictive analytics can be used throughout the organisation, from changing the outcomes and purchasing patterns to identify trends in sales activities.
Predictive analytics finds a wide application to produce CREDIT score. These scores are used by financial institutions and startups to determine the probability of finding customers to making future payments on time.
Use Predictive Analytics when you need to know something about the future, or fill in the missing information or update your records.
Prescriptive is the third and final step of data analytics which comes after descriptive and descriptive analytics. Prescriptive Analytics is more complex than Descriptive and Predictive analytics. Predictive Analytics basically predicts multiple futures at a time and allow companies to assess the number of outcomes-based upon their requirements. Predictive Analytics uses a combination of techniques and tools such as business rules, algorithms, computational modelling procedures, Machine Learning and Artificial Intelligence.
Prescriptive analytics is complex to administer and most companies cannot afford and maintain them for their daily course of business. If predictive analytics is implemented correctly then they can have a large impact on how a business makes important decisions. Larger companies are successfully implementing prescriptive Analytics to optimise production, scheduling and inventory in the logistics and supply chain to ensure the products have been delivered successfully at the right time and optimise the customer experience.
Prescriptive analytics finds a wide application in the field of oil and natural gas. Energy covers about 8 trillion dollars and is the largest industry in the world. An assessment and make a decision-related to oil and natural gas exploration, development and production generate a lot of data. Prescriptive analytics software can help in locating and producing hydrocarbon. Apart from oil and natural gas, Prescriptive analytics find large application in healthcare. Prescriptive analytics is playing a major role to improve the performance in different sectors of healthcare.
Use prescriptive Analytics when you need to provide users with advice on what action yo take.