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Introduction To Predictive Analytics

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Data Analytics Vs Predictive Analytics

INTRODUCTION:
Analytics is the use of data, machine learning, statistical analysis and mathematical or computer-based models to get improved insight and make better decisions. Analytics is defined as “a process of transforming data into actions through analysis and insight in the context of organisational decision making and problem solving.” Analytics is supported by many tools such as Microsoft Excel, SAS, R, Python(libraries). There are mainly three types of analytics: - descriptive analytics, predictive analytics and Prescriptive analytics. Source: Google Image
Descriptive Analytics: This type of analytics is used to summarize or turn …show more content…

With this type of analytics we are able to predict the possible consequences based on different choices possible for an action, it can also be used to find the best course of action for any pre-specified outcome.

Comparison: -
Basis for Comparison Data Analytics Predictive Analytics
Form

Data analytics is ‘general’ form of Analytics used in businesses to make decisions which are data driven. Predictive analytics is ‘specialized’ form of Analytics used by businesses to predict future based outcomes.
Structure Data Analytics consists of data collection and data analysis in general and could have one or more usage. Predictive analytics consists of Defining a Project and data collection, Statistical Modelling, Analysis and Monitoring and then predicting an outcome
Data
Raw data is churned to get clean data for doing Data Analytics. Clean Data is provided for doing Predictive Analytics
Sequence Data Analytics is sequenced as following steps – collect, inspect, cleaning, transforming the data, and reach to conclusions. Predictive Analytics is sequenced as following steps – Model the Data, Trained the Model, Predict and Forecast the outcome . …show more content…

Predictive analytics helps to answer questions such as “what will happen if demand goes down by 10% or if supplier prices go up by 5%?” “What do we presume to pay for fuel for next few months?”” What will be the risk of losing money in a new business enterprise?”

Let’s understand few differences between these two similarly looking terminology –
KEY DIFFERENCES: -
1. Data analytics (DA) involves processing and examining of data sets in order to draw conclusions about the information those data sets consists of. Predictive analytics helps to predict the future by inspecting historical data thoroughly, detecting a patterns or relationships in these data, and then conclude these relationships in time.
2. Data analytics uses tools and techniques to enable businesses to make more-informed, real time and pragmatic business decisions. Predictive analytics can predict risk and find relationship in data not readily apparent with traditional analysis.

3. Data analytics involves finding hidden patterns in large amount of dataset to segment and group data into logical sets to find behaviour and detect trends whereas Predictive analytics involves use of some of the advanced analytics

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