Unlock the business value of enterprise data with in-database analytics Achieve better business results through faster, more accurate decisions White Paper
Table of Contents Executive summary...1 How can you get more timely insights from your data to drive better decision making?...2 SAS and Teradata: Using in-database analytics to deliver timely, trusted insight...3 Our approach...4 Business benefits...5 Customer successes: demonstrating the power of actionable information...6 Large national bank increases marketing response rates and reduces bad debt...6 National retailer achieves double-digit growth...6 Entertainment and gaming company establishes a sophisticated, multi-brand loyalty program...7 Telecommunications company becomes one of the top five carriers worldwide...8 Unlock the potential of your enterprise data today...8 i
Executive summary Consider the myriad of decisions made within your business each day. For example, the staff in your sales and marketing departments might only have: [Information and Knowledge Management] professionals are adopting an emerging best practice known as in-database analytics. Under this practice, data mining, predictive analysis, and other compute-intensive analytic functions are migrating to the EDW platform. In-database DW analytics can either replace or supplement traditional analytics execution approaches. June 2009 report Massive But Agile: Best Practices For Scaling The Next-Generation Enterprise Data Warehouse James G. Kobielus Senior analyst Forrester Research hours to decide which customers are good candidates for tomorrow s 24-hour discount email. minutes to assess the risk of offering credit to a potential new customer. seconds to determine if a long-term customer on hold with your contact center or visiting your website qualifies for special pricing that will help you close a sale today and keep them coming back. Until now, most companies have found it difficult to deliver the secure, accurate and near real-time analytical insight required to support fast decisions like these. This paper explains how you can use in-database analytics to not only accelerate your time to insight, but also gain greater confidence in both the accuracy of your decisions and the security of your data. Predictive Analytics sometimes referred to as Predictive Data Mining is a branch of Business Analytics that uses historical data to make predictions about future events through sophisticated modeling techniques. Increasingly, predictive analytics is being used for critical business purposes, such as: Predicting when a customer might be about to move to a competitor Predicting if a customer would be a likely up sell opportunity Predicting loan default rates and identifying customers in danger of defaulting Predicting future stock prices Identifying fraudulent activities by identifying transactions that deviate from predictions (For instance, credit card transactions that deviate from past behaviors can be flagged and investigated for possible fraud.) Determining risk of illness either to determine insurance premiums or more helpfully to arrange preventative medical programs DATABASE Trends and Applications, Crystal Ball-Gazing With Predictive Analytics by Guy Harrison July 2009 Issue 1
How can you get more timely insights from your data to drive better decision making? In today s economy, growing your business is harder than ever. Even in a strong economy, over a five-year period, it s not uncommon for businesses to lose up to half of their customers. Equally daunting is the fact that acquiring a new customer can cost six to seven times more than retaining an existing customer. These statistics underscore the need for a more holistic view of your customers and operations, as well as timely, trusted insight to enable more agile operations and informed decision making. In the securities industry, certain types of risk, like market risk, happen second by second. Being able to have an architecture that copes with that is going to be vital. David Furlonger VP and investment industry analyst Gartner, Inc. E-Trade Turns to Agile Response Team for Rapid Risk Analysis, Securities Industry News, April 13, 2009 To understand the value of timely, trusted insight, imagine that you are a marketing executive responsible for customer acquisition and retention activities. Without near real-time customer insight, How can you accurately predict what customers will likely buy in time to adjust execution accordingly for example, by developing more targeted merchandizing, pricing, and marketing plans and tactics that directly impact revenue? How can you quickly generate detailed, up-to-date customer profiles and segmentation insight needed to provide call center agents with the right offer for each prospect while they still are on the phone? Similarly, imagine that you are a risk officer at a bank tasked with preventing fraud as well as ensuring that your new customers are trending within a lower risk tolerance. With outdated or inaccurate information, 2
Enterprises have substantially completed their adoption of core BI, enterprise data warehouse, and enterprise content manage ment platforms and will increasingly turn to powerful predictive analytics, data mining, statistical analysis, and text analytics tools to leverage that information for business optimization. One consequence of this trend will be the growing adoption of in-database analytics techniques, under which users will process these compute- and data-intensive functions inside the enterprise data warehouses, taking advantage of that platform s massive parallel processing. James G. Kobielus Senior analyst Forrester Research Experts forecast business intelligence market trends for 2009, SearchDataManagement.com, January 7, 2009 How can you accurately assess each customer s risk and reward potential without creating bottlenecks in your loan origination processes? How can you detect fraudulent activity as soon as it occurs in your portfolio of mortgages, loans, and credit lines before these events cost the bank money? These types of situations are not uncommon. Most companies simply can t aggregate, analyze and process large volumes of data quickly enough to support critical decisions that must be made in hours, minutes or seconds. Nor can they ensure the security of corporate information, because IT has to extract, move and replicate data from an enterprise data warehouse (EDW) prior to analyzing it. This process can take weeks. By the time decision makers receive what they need, the opportunity to make use of it has often passed. As a result, people at all levels of a business are forced to either make decisions based on the analysis of untrusted data or gut instinct. SAS and Teradata: Using in-database analytics to deliver timely, trusted insight SAS and Teradata Corporation have joined forces to develop integrated tools and techniques that make it faster and easier for you to access trusted analytical insight based on the most up-to-date enterprise data. At the heart of this partnership is support for in-database analytics, which enables you to analyze data directly within a Teradata Database without having to extract and move it first. The joint solution boosts data security and accelerates the processes of data preparation, scoring, measurement and reporting by running these processes inside the Teradata system. 3
Why Teradata? Teradata is the leader in data warehousing solutions and has the expertise needed to successfully apply SAS solutions and analytics within Teradata EDWs. Teradata EDWs are powerful, proven systems that offer: A single, integrated view of the enterprisewide data needed to make smarter, faster decisions. Consistent and accurate data at both the detail and summary levels. Scalable parallel database processing that supports nearly unlimited amounts of data and users, as well as simple to complex queries and mixed workloads. Proven data warehousing technology that is flexible and scalable enough to grow with your business needs. Affordable, flexible and proven Teradata Purpose-Built Platform Family to meet diverse business needs across the entire enterprise. By optimizing how your analytics and database technology investments work together to perform their unique but interconnected functions, you can make fast decisions based on the latest data to help you attract and retain customers, grow your business and be more competitive. Our approach SAS has tailored its software to run directly on Teradata systems, so you get more from your data faster and at less cost. Rather than having to pull a massive data set from your EDW and move it to another server for analysis, now you can run and optimize certain SAS software directly within your Teradata Database. Your data is secure, and you get results with far fewer errors than is possible when using the old method of extracting, copying and analyzing data outside the database. Key SAS analytical functions are now able to exploit the core Teradata parallel architecture, giving you significant improvements in speed and performance. Equally important, you can trust the results of your analysis because they are always based on the most current data available. As a result, you can get reliable answers to your urgent business and customerrelated questions in hours, minutes or even seconds. For example, deploying the SAS model scoring logic directly within the Teradata Database engine significantly increases processing speed and performance, reduces model re-work time and enables you to get the information and insights you need faster. Results that used to take days or weeks can be completed in an hour. This means you can potentially: Reduce costs and time to insight from, in some cases, 40 days down to one day. Make the next best offer while customers are still in front of sales people. Measure potential spend and profitability before customers leave your site. Identify and manage non-performing assets (mortgages and loans, for example) and prospective customers by integrating risk management into daily business activities. Receive alerts regarding criminal or fraudulent activities before transactions are complete. Respond to changing customer preferences (what s trendiest, cheapest, etc.) in minutes versus weeks. 4
Why SAS? SAS is the leader in business analytics software and services, and the largest independent vendor in the business intelligence market. Through innovative solutions delivered within an integrated framework, SAS helps customers at more than 45,000 sites improve performance and deliver value by making better decisions faster. Since 1976 SAS has been giving customers around the world THE POWER TO KNOW. These are clearly the kinds of capabilities that customers have been asking for and analysts are excited about. Dan Vesset, Program Vice President for Business Analytics Research at IDC, had this to say when the SAS and Teradata in-database analytics initiative was announced: Today s businesses are challenged to manage huge data volumes while optimizing analytical model development and deployment environments. In-database analytics enables IT and analysts to be more productive and responsive to the growing demand by business decision makers for analytics-based strategic and operational decision support. Today s announcement shows that SAS and Teradata are closer to delivering on the promise of in-database analytics, which is to give customers an efficient, powerful means for implementing predictive analytics and information analysis in one location. The in-database analytics solutions discussed in this announcement are available today and in use by leading companies around the world. Business benefits Our combined efforts give you the powerful analytics, speed and reliable data you need to make informed decisions quickly, as well as power sophisticated personalization strategies executed by your sales and marketing department. As a result, you can: Significantly reduce the time needed to answer business questions. Gain near-instant insight needed to drive personalization and other customercentric strategies. Improve data quality, availability and consistency, so you can trust the insight obtained through the analysis. Gain insight into trends, risks and opportunities, and respond swiftly to improve business outcomes. Free up staff to focus more time on value-adding activities. 5
Customer successes: demonstrating the power of actionable information As the following customer examples illustrate, in-database analytics enables faster, more informed decisions that help you retain customers, manage risk, grow your business and compete more effectively. Large national bank increases marketing response rates and reduces bad debt When a large national bank faced increasing competition and complex compliance challenges, management developed a comprehensive plan of attack: integrate data across business lines, increase marketing response rates, reduce bad debt on credit cards and help business analysts work more productively. To help reach these goals, the bank uses SAS and Teradata technology to consolidate data and segment customers. Now that analysts are no longer spending 80 percent of their time pulling data together, regulatory requirements are easier to meet, and there is more time to focus on improving the bank s bottom line. For example, leveraging data from third-party marketing partners, the bank can rank customers by lifetime value and make timely offers that match customers needs, resulting in an increase in response rates from less than one percent to 20 percent. To strike the right balance between risk and reward, the bank now analyzes each customer s risk profile, along with their needs and propensity to respond, prior to sending out offers. The bank also segments late-paying customers to determine methods to help those customers reduce their debt. This approach has enabled the bank to reduce bad debt by five percent. National retailer achieves double-digit growth Over ten years ago, when a national retailer specializing in outdoor merchandise was making the move from being primarily a catalog company to a growing, multichannel business, it needed deeper and faster insight into customer preferences and buying patterns than its homegrown IT systems could support. Previously, analysts had to spend one to two weeks per month just bringing together disparate data sources. Now, with the integration of SAS and Teradata, data is available in seconds rather than days or weeks. Statisticians can build models faster, have more time to uncover high-value business insights, and leverage up-to-date insight to optimize real-time customer interactions. For example, they can more quickly: 6
Choose up-sell offers and schedule promotions to drive sales. Identify potentially profitable new prospects before the competition does. Help customer service reps personalize their interactions based on each customer s value. Identify each customer s favorite channel to selectively send related marketing materials. Focus marketing efforts on the most profitable geographies, an approach that has boosted response rates by 60%. The retailer is currently in the process of using in-database analytics to identify the clickstream patterns of online customers so they can put the perfect offer in front of them in real-time based on the historical patterns of similar shoppers. Entertainment and gaming company establishes a sophisticated, multi-brand loyalty program One of the leaders in the entertainment and gaming industry had used SAS software and a Teradata system for years, leveraging predictive analysis and business intelligence to encourage their best customers to return again and again. Prior to adopting in-database analytics, analysts had to retrieve data from the warehouse, organize and normalize the information and build predictive models. Today, they can analyze data directly within the Teradata system, enabling lighteningspeed analysis. Hot players, for example, are monitored in real-time and offered targeted up-sells while they are on the gaming floor. This requires nearly instant analytical processing speeds of data collected in real-time, which is only possible with in-database analytics. As a result, customers are better serviced, and the business is more profitable. The program helps the company s staff treat all of their best customers not just the high rollers like VIPs. Customers really appreciate the fact that this company knows them better than they would expect. And because the company can quickly recognize what stage of the relationship they re in, they can approach each customer with timely offers that are most relevant to them. It s no surprise that the company s rewards card is the most sophisticated, national multibrand loyalty program in the industry. 7
Telecommunications company becomes one of the top five carriers worldwide The largest mobile carrier in the UK is using an integrated SAS and Teradata solution to help them achieve their goal of becoming one of the top five carriers worldwide. Prior to implementing the new solution, fragmented data volumes had grown exponentially, and it was taking approximately 40 days for management to access the customer insight needed to help drive growth. The company faced everchanging customer demands, increasing churn risks and intensifying competition. But it lacked access to the timely insight needed to respond to customer needs swiftly and in a personalized way. In-database analytics has enabled the company to reduce the cost of using analytics and reduce the speed of information delivery from 40 days to one day. Now the telecommunications company can: Identify customers most likely to churn early enough to offer them the best services and plans to keep them from defecting to a competitor. Drive the most meaningful content specific to each subscriber. Shorten the time required for the company to execute marketing plans by integrating its customer data warehouse from Teradata with SAS analytics. Improve the turnaround time of decisions on pricing, promotions and content for improved customer satisfaction. Unlock the potential of your enterprise data today For organizations whose success or failure depends upon accurate and timely decision making, integration of database and analytical capabilities can make all the difference and lead to greater profitability and growth. SAS and Teradata Corporation have taken the investment in their strategic partnership to the next level and created the SAS and Teradata Analytic Advantage Program to offer in-database analytics. This program provides competitively priced, integrated packages that enable you to quickly and cost-effectively implement and deploy SAS Business Analytics with the Teradata Enterprise Data Warehouse platform. 8
The SAS Analytic Advantage for Teradata offering includes three different packages Express, Advanced and Enterprise to meet your growing analytic needs. Each of the three packages is paired with the Teradata data warehousing package corresponding to your requirements, providing a powerful foundation for analytic processing. SAS and Teradata have also created The SAS and Teradata Center of Excellence, which features a dedicated team of solution architects and technical consultants to help you use our solutions to optimize the performance of your existing and future infrastructure around in-database analytics. Services include architecture assessments and recommendations, proof of concepts, benchmarking and sizing analyses, and customized consulting. Are you ready to transform business decision making through the power of indatabase analytics? For more information, please see the SAS and Teradata Analytic Advantage Program Website: www.sas.com/technologies/analytics/advantage.html 9
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