Best Predictive Analytics Software include:
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Predictive Analytics Software Overview
What is Predictive Analytics Software?
Predictive Analytics are used to analyze current data and historical facts in order to better understand customers, products, and partners. It is also used to identify potential risks and opportunities. Predictive analytics platforms tend to be very complex products and require advanced skill sets in order to use them effectively.
In the hands of skilled data analysts and data scientists, predictive analytics can be an extremely powerful tool. It can, for example, calculate customer lifetime value for a given customer; estimate sales projections for the next quarter, or predict what product an online shopper is likely to purchase next.
The Importance of Good Data
The basis for good predictive outcomes is good data. For example, to make predictions about what customers are likely to buy in the future, it's essential to have detailed data on what they have bought in the past, attributes of purchased products, etc.
Provided there is adequate high-quality data, predictive models are created using techniques like regression testing, decision trees or other methodologies to measure degree of correlation between variables to help predict future behavior.
Predictive Analytics vs. Business Intelligence
Predictive Analytics tools are strongly related to Business Intelligence, and they are sometimes considered as part of the BI universe. The distinction between BI and predictive analytics is that BI is usually considered descriptive, i.e. looking at what happened in the past. Predictive analytics is about finding hidden patterns in data using complex mathematical models to predict future outcomes.
The emergence of big data platforms like Hadoop and very fast in-memory analytics products has resulted in some blurring of the lines between big data and predictive analytics.
A couple of well-known incumbent products own the lion’s share of the market and these tools tend to be much more expensive than newer upstart products with much smaller market share. One of the leading products in the category costs over $5,000 per user. Newer, less well-known products typically cost a fraction of the cost of the market leaders.
The free, open-source R programming language has more than 3,000 community-developed analytical applications, but can be challenging to use since it is code-based and does not have a drag-and-drop visual workspace.