Tuesday Feb 25, 2014

Big Data and Analytic Top 10 Trends for 2014

Oracle’s Top 10 Big Data and Analytics Trends for 2014 are now here!  Read what hundreds of IT decision makers are saying about their big data and analytics plans in mobile, cloud, Hadoop, discovery, predictive, and decision optimization technologies, practices, and skills.

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Thursday Jan 31, 2013

Using In-Database Analytics to Predict Fraud

Your data warehouse stores critical data telling you what is happening in your business and sometimes why it’s happening. But you can go beyond understanding why something went wrong. You can use past data to predict the future, correcting problems before they happen. In a recent survey that Oracle did of over 300 C level executives, 93% of them thought that their companies were losing an average of 14% of their total revenue because they couldn’t fully leverage the information they had already collected. One key way to do this (and you’ll hear more about this in a future survey) is to use predictive analytics. Let’s take a quick look at why and how.

Turkcell is a leading mobile phone provider in Turkey, with over 34 million subscribers. And like most mobile providers a majority of those subscribers use pre-paid accounts and pre-paid cards. Money launderers take advantage of this, and losses for this business are of the order of $5 for every $10,000. This may not seem like much, but with billions of transactions, this adds up to millions of dollars a year.

Like other companies, Turkcell examine huge quantities of data and build models that help it identify and ultimately predict and prevent fraudulent transactions.  Unlike many other companies, Turkcell does this analysis in its data warehouse. With 100 TB of compressed data – representing over a petabyte uncompressed – it would take a long time to move that data out of the warehouse and keep it up to date as new data arrived. And the window to stop the next fraudulent transaction might have already closed.

Oracle Advanced Analytics enables you to perform sophisticated predictive analytics inside a data warehouse. You can mine your data directly while it is inside the Oracle Database using either SQL or R language APIs or the Oracle Data Miner SQL Developer “work flow” GUI extension, depending on your need and existing skills. You build models for past behavior and use that to predict future behavior, improving your accuracy with time. And best of all, there’s no need to move the data around which takes time you might not have and also leaves you exposed to security risks. As Turkcell said “...we can analyze large volumes of customer data and call-data records easier and faster than with any other tool”

Friday May 18, 2012

The Art of the Possible with Business Analytics

It has been established beyond doubt that data and its analysis can have a huge impact on an organization’s top line and bottom line. Business Analytics helps organizations deliver better business performance in two ways – by optimizing business processes and by helping to innovate. Optimization helps organizations be efficient and effective by taking inefficiencies out of the business processes and focusing on the high impact opportunities. Innovation on the other hand helps organizations by uncovering new customer segments, new product categories, new markets, new business models etc.

The styles of analyzing data are many fold from answering questions like “what is going on?” to “why are the things the way they are?” to “what will happen if I do X or Y?” to “what does the future look like?” Broadly speaking the styles of analytics can be classified into three categories:

·         Exploratory Analysis: The objective of exploratory or investigative analysis is exploration and analysis of complex and varied data – whether structured or unstructured for information discovery.  This style of analysis is particularly useful when the questions aren’t well formed or the value and shape of the data isn’t well understood.

·         Descriptive Analytics: The objective of this style of analysis is to answer historical or current questions like what is going on. why are the things the way they are?. This is the most common style of analysis and here the questions as well as the value and shape of data are well understood.

·         Predictive Analysis: Predictive analysis aims at painting a picture of the future with some reasonable certainty.

So, what’s art of possible with business analytics? It’s the application of the above three styles of analytics to a business scenario for better insights, decisions and results. Let’s try and explain this with an example. Consider this scenario:

You are a Financial Services firm e.g. a large bank and are trying to improve profitability. You read Larry Seldon’s book titled “Angel Customers and Demon Customers” and agree with the findings that 20% of your top customers bring in 80% of the profits and would like to manage you business as a portfolio of customers as opposed to portfolio of products. So, how do you do that? The answer is business analytics.

You can start by using descriptive analytics techniques like operational reports, ad-hoc query, dashboards etc. on data collected from different sources like sales, customer service etc. to determine the profitability of each customer. You can then use predictive analysis techniques like data mining, statistical analysis to further enrich your customer data into profitability segments like high, medium, low and loss making customers. Finally, you can choose different customer service channels like personal banker, phone or ATM to cost effectively serve you customers e.g. a high profitability customer can be served by a personal banker free of charge but if the loss making customer wants a personal banker there will be a charge. Once you have implemented such programs you can use exploratory analysis to gauge the sentiment across social media channels like Facebook and Twitter to see if the programs are working as desired. Better yet you may come up with new innovative business models like mobile banking or online only banking to improve profitability.

That’s the art of possible powered by business analytics. Stay tuned, I intend to publish more examples from different industries to show the art of possible with business analytics.
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