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Anyone and everyone today who talks about Big data talks about Predictive Analysis. I am looking for insights into the same.
If you mean big quantity data i think with Predictive analysis it will lead to real useful data. I think that they are strongly related to each other, because big data should be analize carfully and predictivity to result a clear and usef data that can be used for decision making.
For the big quality data i think that with Predictive analysis it will give a perfect result with all the details need for any decision.
But the main question when we can said that this is a big quality data?
What's predicted: The kind of behavior (i.e., action, event, or happening) to predict for each individual, stock, or other kind of element.
What's done about it: The decisions driven by prediction, the action taken by the organization in response to or informed by each.
When you say big data it means data of many years recorded and stored correctly. The challenges include capture, curation, storage, search, sharing, transfer, analysis and visualization of DATA. There are many tools available to sort and use data in a meaningful manner. Once you have correct data warehouse at your disposal you may use Business Intelligence tools to extract the way you want. This may include future/predictive analytics.
Connectivity between the two :
Predictive analytics is an enabler of big data : Businesses collect vast amounts of real-time customer data and predictive analytics uses this historical data, combined with customer insight, to predict future events. Predictive analytics enable organizations to use big data (both stored and real-time) to move from a historical view to a forward-looking perspective of the customer.
For example, stores that use data from loyalty programs can analyze past buying behavior to predict the coupons or promotions a customer is most to participate in or buy in the future. Predictive analytics could also be applied to customer website browsing behaviors to deliver a personalized website experience for the customer.
Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.
First of all this is important to understand that what is predicitive analysis it means which the company can seen and what the company wants as a result this is predictive analysis now for that you have to handle all the thigs
Now how would you handle for it you need the department where mistakes is going on and now comes how can you predict that this department is faulty
through the big data
now for predictive analysis big data is mandatory
The most important is saving time and human energy so that we can make future plans early
The terms Predictive analytics, Data analytics, data science, and analytics are often used interchangeably. They all tend to mean the same thing: the science that applies statistical (machine) learning to transform data in databases to useful insights that decision makers can use to make better decisions.
As for Big data, it is just a term to indicate that data is too big for your computer's RAM. In other words its size is greater than the RAM. So this is basically a naive and relative term. My computer could handle4GB while a supercomputer might be able to handle1PB (petabye). But in general it's data that cannot fit in the average computer. The term is also used to indicate the floods of data we are producing. If you think of it for a minute there is a huge amount of data being produced by each one of us from Twitter & Facebook to marketing & business data.
To deal with data that doesn't fit in computer's RAM several methods could be utilized. Two popular are to chunk data and save it on the harddisk and retrieve only a small sample that can fit in the RAM. Another is to distribute the data to many computers and having each process the data and relay the result back to a single computer.
Hope this answers your question and clears any confusion.
Big Data and Predictive analysis go hand in hand since we you the big data to carry out the predictive analysis. We cannot project without prior knowledge
