OVERVIEW
What is predictive analytics?
Predictive analytics is a branch of advanced analytics that makes predictions about future outcomes using historical data combined with statistical modeling, data mining techniques and machine learning. Companies employ predictive analytics to find patterns in this data to identify risks and opportunities.
Predictive analytics is often associated with big data and data science. Companies today are swimming in data that resides across transactional databases, equipment log files, images, video, sensors or other data sources.
Analytics Strategies
To create a robust data and analytics strategy, business leaders need to consider many factors. Here are the critical points I would expect to see in a strong data strategy:
- Reduce Costs and Save Time
- Mitigate Business and Policy Risk
- Increase Revenues and Margins
Project Plan Steps
Many people believe that data-driven research is only conducted in the sciences. It’s commonly considered to entail a spreadsheet full of numbers. Both of these assumptions are false. Research data is collected and used in scholarly work across many academic disciplines, and while it can be as simple as figures on a spreadsheet, it can also be more complex.
Data Consulting
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Big Date & AI
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Quantitative Algorithms
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Requirements engineering
Defining functional and non-functional requirements for a BI solution. These requirements can be further classified into two groups – mandatory and optional.
Analyzing the existing business needs and analytics environment; eliciting the requirements for the future BI solution.
Defining deliverables, assessing risks, estimating BI implementation costs, TCO and ROI. After fulfilling this step, you get a detailed project plan, a project schedule and a communication plan.
- Reduce Costs and Save Time
- Mitigate Business and Policy Risk
- Increase Revenues and Margins