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Month: July 2016

Top 10 Predictive Analytics techniques ?>

Top 10 Predictive Analytics techniques

Predictive Analytics translates Big Data into meaningful, usable business information. Numerous techniques can be used for Predictive Analytics but there are 10 that lead the way. The Data Warehousing Institute surveyed 373 companies to analyse what are the most used Predictive Analytics models and algorithms. The result is:

Top 10 Predictive Analytics techniques

Decision trees and linear regression are the most common. Both methods are relatively easy to understand and straightforward. Linear regression,widely used in statistics, tries to model the relationship between variables by fitting a line to the observed data.… Read

Predictive Analytics ecosystem ?>

Predictive Analytics ecosystem

Predictive Analytics ecosystem

Data sources

Databases

Structured

Unstructured

Applications

Sales

Marketing

Product

Customer

3rd party data

Business info

Social Media

Web Scrapers

Public data

Data wrangling

Enrichment

Human

Automated

Blending

Data integration

API connecetors

Data applications

Insights

Statistical tools

Business Intelligence

Data Mining / Exploration

Data Collaboration

Models

Predictive Analytics

Deep Learning

Natural Language Processing

Machine Learning Platforms

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Predictive Analytics Quick Info – Myth: We do not have enough data ?>

Predictive Analytics Quick Info – Myth: We do not have enough data

This is a very common misconception about Predictive Analytics. Many people think they do not have enough data to do Predictive Analytics. But the reality is all companies store data in one way or another. If you have data, you can do Predictive Analytics. It does not matter if you have a Data Warehouse, a Data Base or raw text files. Also, do worry about the amount of data.

Tip #1: quantity is not quality

Even companies with a huge amount of data need to break it into smaller pieces.… Read