Faster Business Insights By Enabling Real-Time Data for Business Intelligence (BI) & Analytics A Best Practices White Paper

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1 Faster Business Insights By Enabling Real-Time Data for Business Intelligence (BI) & Analytics A Best Practices Page 1 of 11

2 Executive Summary In today s intelligent economy, companies must analyze and act upon information to gain competitive advantage. Accessing and analyzing the right information at the right time can increase customer profitability and satisfaction, reduce time to market, prevent fraud, and aid with regulatory compliance. The key to success with BI and analytics initiatives is timely data. Yet, many IT teams struggle to provide fresh information to employees, customers, and business partners. Corporate IT teams are faced with enormous volumes of structured and unstructured data that must be integrated from many different sources. In addition, traditional data warehouses simply aren t designed to support real-time information updates. Conventional ETL tools also have major shortcomings. Batch processes require IT oversight for scheduling and management, and business users still end up waiting for fresh data. A variety of best practices can help organizations overcome these obstacles. Management teams must develop a business analytics strategy and define what right-time data means for the organization. On the technology side, IT teams should create a dedicated lowlatency data warehouse for BI and analytics, and use log-based change data capture and replication tools to support low-latency data movement. Page 2 of 11

3 Table of Contents EXECUTIVE SUMMARY 2 THE INTELLIGENT ECONOMY IS CHANGING THE WAY COMPANIES DO BUSINESS. 4 WHY DO IT TEAMS STRUGGLE TO PROVIDE BIZ USERS WITH REAL-TIME DATA...6 BEST PRACTICES FOR REAL-TIME BI AND ANALYTICS. 7 Develop a business analytics strategy. 7 Implement the business analytics strategy in an incremental way 7 Define what right-time data means for the organization 8 Consider creating a dedicated low-latency data warehouse for BI & analytics.8 Use CDC and replication tools as a complement to ETL & batch processes 8 Select a log-based CDC tool for low-latency data movement.8 HOW CAN ATTUNITY HELP...8 Solution 1: Attunity Replicate 9 Solution 2: Attunity Connect.10 ABOUT ATTUNITY.11 Page 3 of 11

4 Companies in every industry sector are striving to make better decisions faster than their competitors. More data is available than ever before to support business intelligence and analytics, but IT teams have discovered that integrating large volumes of information and providing it to business users in real-time is very challenging. Although enabling real-time data may seem daunting to IT leaders, low-latency data warehousing in combination with change data capture and data replication tools offer a low-cost, highly usable alternative for meeting today s business decision-making needs. The Intelligent Economy Is Changing the Way Companies Do Business In today s business world, it s not enough to simply access information about commercial transactions. True value and competitive advantage come from analyzing and acting upon information. According to Dan Vesset, Program Vice President of Business Analytics Research at IDC, the world is shifting from the information economy to the intelligent economy. 1 To feed company-wide BI and analytics initiatives, organizations must provide users, customers and partners with consistent access to fresh information. Depending on the business process, the required frequency of timely information can range from weeks to hours to real-time updates. Research shows that top performing companies recognize how important up-todate information is for business performance. A study by the MIT Sloan Management Review and the IBM Institute for Business Value revealed that 58 percent of organizations apply analytics to create a competitive advantage within their markets, up from 37 percent a year ago. These companies are more than twice as likely to outperform their peers. 2 Analytics Versus BI Analytics and BI are widely used terms, but confusion exists about how these activities differ from one another. Gartner defines BI as the general ability to organize, access, and analyze information to learn and understand the business. 3 Traditionally, BI has been used for performance reporting and as a planning and forecasting tool. 4 Access to realtime, historical data for both of these BI applications improves their effectiveness. In contrast, analytics leverage data to enable context specific insights that are actionable. Many industries use real-time data for analytics, in order to make faster decisions. 5 Examples of analytics include predictive analytics, text mining, and customer analytics. 1 Low-Latency Data Warehousing: Answering Big Questions About Big Data. IDC Analyst Connection, August Analytics: The Widening Divide. MIT Sloan Management Review Research Report, Fall Page 4 of 11

5 In the new intelligent economy, companies need to access and analyze the right information at the right time to meet a variety of business needs: - Increase customer profitability and satisfaction. By aggregating and analyzing customer information, companies can develop a more complete and accurate view of buyer behavior. Analytics is used to predict customer purchases based on buying habits and preferences, reveal upsell and cross sell opportunities, segment consumers for marketing campaigns, profile customers for retention programs, and more. McKinsey Global Institute suggests that retailers can increase operating margins by more than 60 percent through better utilization and analysis of big data. 6 - Reduce time to market. Through the use of concurrent engineering practices, manufacturing firms integrate data from their research and development teams, engineering units, and factories. By analyzing data from multiple sources, these companies manufacture higher quality products and bring them to market faster. - Prevent and detect fraud. During tough economic times, companies experience higher levels of fraud. The Global Retail Theft Barometer 2011 found that shrinkage at retail businesses reached $119 billion, an increase of 6.6 percent from This increase is attributed to higher levels of shoplifting, employee fraud, and organized retail crime. Fraudulent credit card transactions and identity theft are serious problems. Real-time analytics and data mining can be used to identify unusual patterns which point to illicit activity. By identifying fraud early, firms can take proactive steps to prevent further losses. Merchants that accept Visa and Mastercard payments, for example, must conform to the Payment Card Industry Data Security Standard (PCI DSS), which provides a framework for preventing, detecting, and reacting to security incidents. - Comply with government regulations. Regulations worldwide require companies to access timely and relevant business information which can be analyzed and reported upon for compliance purposes. In the United States, the healthcare sector is dealing with healthcare reform legislation, while the financial services and insurance industries must comply with new and existing regulations. For example, the Federal Insurance Office was created by the 2010 Dodd-Frank Wall Street Reform and Consumer Protection Act to monitor all aspects of the insurance industry. In addition, under the Sarbanes-Oxley Act (SOX), publicly traded companies and public accounting firms must have internal controls to guarantee accurate and timely financial reports and disclosures of material Page 5 of 11

6 changes in financial condition. In 2012, the United Kingdom s Retail Distribution Review will be implemented, affecting investment advisers commissions and qualification requirements. The answer to many of these business challenges is enabling user access to real-time data to support BI and analytics. This was evident in an IDC study of more than 1,000 organizations worldwide which found that industry leaders are almost 1.5 times more likely than their peers to feel that their data warehouse updates are sufficient to meet their business needs. 8 Why Do IT Teams Struggle to Provide Business Users With Real-Time Data? Although up-to-date information is essential for effective decision-making, many IT teams struggle to provide that data to the business. One issue is that big data has changed the way organizations manage information. Companies capture enormous amounts of customer, supplier, and operations-related data. In addition, networked sensors in devices ranging from mobile phones to cars also generate and communicate information. This volume of data is becoming difficult to manage and analyze using traditional database software tools. A recent study by McKinsey Global Institute reported that the amount of global data generated per year is expected to grow by 40 percent, while global IT spending is only projected to increase by five percent. 9 Out of 17 industry sectors in the United States, 15 have more data stored per company than the U.S. Library of Congress. 9 Corporate IT teams face three major challenges when it comes to providing real-time data for BI and analytics: 1. Data must be integrated from many different sources. The information that business units need for BI and analytics often resides in numerous systems, including legacy systems and data sources that are outside the organization. It is common for information to exist in many different formats, structured and unstructured, thereby making the integration process complex. 2. Traditional data warehouses aren t suited for low-latency data movement. Demand for up-to-date information is driving the need for low-latency data warehousing. Batch loading of data is inadequate because it fulfills only simple reporting requirements, based on predefined and static rules and policies. 3 Gartner IT Definitions and Glossary ( 4 Gartner Says BI and Analytics a $10.5 Bln Market. July 7, 2011 ( 5 Analytics buzzword needs careful definition. February 7, Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute, June The Global Retail Theft Barometer The Centre for Retail Research at the University of Nottingham. Page 6 of 11

7 3. Conventional ETL tools have significant shortcomings. Too often, IT teams try to use traditional ETL tools for every type of data movement, rather than finding solutions that are more appropriate for feeding data warehouses in real-time. Batch processes create operational complexity. As resources schedule and manage large batch windows, business users experience unproductive wait times for fresh data. Fixed integration execution schemes impede right-time data access. Some organizations use application integration techniques where applications make changes and the changes are integrated through a fixed integration execution scheme. This approach is problematic because database contents must be coordinated as changes are made, requiring software to work with each database system. This results in a delay between when a change happens and when it appears in the data. Business users are unable to access current information as quickly as desired. A survey by IDC found that only 17 percent of organizations are very satisfied with the performance of the data warehouse loading process. 8 Best Practices for Real-Time Business Intelligence (BI) and Analytics To enable real-time data for BI and analytics, IT teams should consider the following best practices: Develop a business analytics strategy. A good first step is to create a business analytics strategy. This strategy should include the types of business decisions made in the organization and identify the user groups involved in making the decisions, as well as the affected business processes. By understanding where low-latency data warehousing is required, IT teams can develop a business case for technology investments. Implement the business analytics strategy in an incremental way. It is prudent to use an initial BI or analytics project to demonstrate that real-time data can be delivered, rather than implementing an organization-wide solution. When IT meets the business requirements for up-to-date data, it builds trust with business users and promotes more rapid execution of new analytics projects. 8 Low-Latency Data Warehousing: Answering Big Questions About Big Data. IDC Analyst Connection, August Big data: The next frontier for innovation, competition, and productivity. McKinsey Global Institute, June Page 7 of 11

8 Define what right-time data means for the organization. Certain business processes require real-time data, while others do not. IT teams must look strategically at company priorities to determine which business processes would benefit most from low-latency data movement, reducing costs. Examples of processes requiring same day decision cycles include customer service, supply chain management, and logistics optimization. Consider creating a dedicated low-latency data warehouse for BI and analytics. Low-latency data warehousing is well suited for moving large volumes of data from diverse operational systems to a single enterprise data mart. There are several benefits associated with low-latency data warehousing technology. Because it eliminates data staging steps, costs related to data extraction, cleansing, and loading are reduced. In addition, continuous data warehouse feeds can decrease the number of batch ETL jobs. As a result, fewer technology resources must be dedicated to data integration and migration tasks. Use change data capture (CDC) and replication tools as a complement to ETL and batch processes. The most common technology used for low-latency data movement is change data capture (CDC). Although many different approaches exist for CDC, every solution processes only the data that has changed, and all transfer data in both frequent and real-time modes. CDC is a good complement to ETL and other batch processes. ETL is a smart choice for slowly changing data that can be refreshed on a scheduled basis, while CDC or replication tools are ideal for rapidly changing data that is needed for critical business decisionmaking. Data replication technologies are optimized for copying data quickly, with minimal or no transformations done before data is sent to the data warehouse. Both CDC and data replication support the shift from ETL (extract, transform, load) to ELT (extract, load, transform). Select a log-based change data capture tool for low-latency data movement. Not all CDC tools are created equal. Some CDC products use agents on the database server, while others use stored procedures. Neither approach is preferred, since both negatively affect database performance. The best method is to drive the data change function off the database log. Log-based CDC tools do not interfere with the database server or add to its load. How Can Attunity Help? Attunity Replicate and Attunity Connect enable organizations to access information when and where it is needed at a significantly faster time to value. These tools allow IT teams to move large volumes of relevant data into a single enterprise data warehouse and simplify access to timely information to support BI, analytics and reporting. Page 8 of 11

9 - Attunity Replicate incorporates both CDC and data replication technologies. It ensures that IT teams can provide up-to-date information to meet business operations and BI needs. Data replication is supported from many enterprise databases including Oracle, SQL Server, and DB2. In - addition, Attunity Replicate is the first data replication software to load data to SQL Azure for cloud data replication. Easy to use. The innovative Click-2-Replicate design simplifies the user experience by automating the steps required to build a replication solution. Simply select your data source, select your target and then click-2-replicate. It s that simple. Plus, all three aspects of database replication are supported (schema and DDL replication, snapshot replication (full load), and delta replication (incremental load)). The packaged software approach is fast to learn and implement. Efficient use of system resources. The zero-footprint technology is designed to reduce the impact on IT operations. This capability eliminates the need to install an agent on source and target database servers to improve performance and reduces the costs associated with upgrades and maintenance. Fully configurable and manageable. Table selection, column selection, and row-based filtering are supported, as well as pattern-based filtering for tables and records. Mapping is possible for calculated columns and column transformation. A management dashboard allows IT teams to quickly scan metrics and alerts. Efficient high performance data replication. Data replication can be optimized using snapshot and transactional data replication which scales to thousands of tables. Optimize resources by only replicating the changes to the data, which enhances performance. Streamlined management of enterprise deployments. A centralized web-based management console makes managing enterprise deployments easy, saving time and expense. Attunity is now one of the core components of our new established service-oriented architecture at JM Family, providing an architecture with increased flexibility and integrated components for bi-directional updates. In addition to the time and money we are saving by not having to develop and maintain custom solutions, we have also cut costs by leveraging some of our legacy applications with new and enhanced distributed applications. Vice President, Technology Delivery and Architecture, JM Family Enterprises, Inc. Page 9 of 11

10 - Attunity Connect provides out of the box, real-time, standard and seamless connectivity to a wide range of relational and non-relational data sources on platforms ranging from Windows to mainframes. Universal SQL connectivity. Attunity Connect offers out of the box ODBC, JDBC, OLE DB and ADO.NET connectivity to enterprise data. Modernize data access quickly and cost effectively. Attunity Connect Application Adapters turn existing business logic into reusable services, allowing applications to be integrated, migrated, and modernized quickly and cost effectively. The reusable services can be used from Java and.net applications, as well as from leading integration infrastructure, including Oracle Fusion Middleware and Microsoft BizTalk Server. Easy to configure and maintain. Using straightforward configuration, Attunity Connect drivers and providers make enterprise data sources seamlessly available by Java,.NET, and web applications, as well as reporting, business intelligence, and data integration platforms. This frees up valuable IT resources to focus on more strategic, higher priority projects. Attunity Connect is very straightforward to use. It gives us the highquality data we need to turn internal business processes and fixed resources into flexible commercial services. Convergence Programme Manager, Lloyd s of London Page 10 of 11

11 About Attunity Attunity is a leading provider of real-time data integration software that enables organizations to access information when and where it is needed. Attunity software solutions include data replication, real-time change data capture (CDC) and real-time data connectivity, as well as enterprise file replication and managed-file-transfer (MFT) offered through our RepliWeb division. Using Attunity s software solutions, our customers enjoy dramatic business benefits by enabling real-time access and availability of data and files where and when needed, across the maze of heterogeneous systems making up today s IT environment. Attunity has supplied innovative software solutions to its enterprise-class customers for nearly 20 years and has successful deployments at thousands of organizations worldwide. Attunity provides software directly and indirectly through a number of partners such as Microsoft, Oracle, IBM and HP. Headquartered in Boston, Attunity serves its customers via offices in North America, Europe, and Asia Pacific and through a network of partners. For more information, call us at or , visit us at and join the Attunity community on Twitter, Facebook and LinkedIn. Visit to learn more about the Attunity data integration software. Contact Attunity at or call (800) (toll free) / +1 (781) Use the following links to join or follow Attunity s online communities: Page 11 of 11

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