TRANSFORM YOUR BUSINESS
Nowadays, companies have data but do not know what to do with these data, and they often face challenges in understanding customer behavior patterns, purchases, and their responses in buying products.
Predictive Analytics is a form of advanced analytics that uses current data and historical data to forecast different activities, customer behaviors, and future trends. It uses many techniques data mining, statistics, data modeling, machine learning, and artificial intelligence.
PREDICTIVE ANALYTICS LIFECYCLE
IDENTIFY / FORMULATE PROBLEM
To get the expected results from Predictive Analytics modeling, it is essential to identify the business objectives/problems, the scope of work, expected outcomes, and data sets to be used in the project.
Typically business owners, business managers, domain experts, one who takes a decision are involved in evaluating the processes & measure ROI in this process.
SATA DATA PREPARATION & EXPLORATION
Before the development of predictive analytic models, Analysts collect data from multiple data sources, clean the data, and consolidating the data for analysis. It’s combined and stored in data warehouses.
Next, they access the data and determine how they want to organize it and check how many cases are available in datasets, what variables are included, missing values of the variables and their possibilities to meet business objectives through the datasets.
TRANSFORM & SELECT DATA
Relevant data is selected, retrieved, and mapped correctly from one format to another, usually from the size of a source system into cleansed, validated, and ready-to-use form. It, also known as ETL (Extract/Transform/Load) process.
BUILD, VALIDATE & DEPLOY MODELS
The process of building a predictive model requires inputs from business stakeholders and data scientists. Usually, Data scientists build multiple predictive analytics models and then select the best one based on their performance while building models.
EVALUATE / MONITOR RESULTS
After a predictive model is chosen, it is deployed into everyday use, monitored to make sure it’s providing the expected results and revised as required. Typically, domain experts, business managers are involved in evaluating the processes and ROI in this process.
TOOLS & TECHNOLOGIES WE USE
ELK STACK
The ELK Stack allows the user to take data from any source, analyze it, and visualize it.
MICROSOFT POWER BI
Power BI provides business intelligence capabilities and interactive visualizations with an interface that helps end-users to create their reports and dashboards.
R SOFWARE
It is a programming language and a statistical computing environment.
RAPIDMINER
RapidMiner is a platform that provides an environment for text mining, machine learning, predictive analytics, data preparation, and deep learning.
APACHE SPARK
It is an open-source distributed general-purpose cluster-computing framework.
TABLEAU
Tableau Public is a service that allows you to publish interactive data visualizations to the web helping users share their reports and dashboards.