Indiana University Improves Strategic Decision Making Across the Organization Using Data Virtualization

• 应用基础设施与中间件 - 数据可视化
• 应用基础设施与中间件 - 数据库管理和存储
• 平台即服务 (PaaS) - 数据管理平台

• 教育

• 商业运营
• 人力资源

• 数据科学服务
• 系统集成

Indiana University (IU) was facing challenges in improving decision making at all levels within the university due to the lack of availability of timely, relevant, and accurate information. Data and its corresponding business logic were stored across multiple, siloed systems, making it extremely time consuming to gather and combine the relevant information decision makers needed. In some cases, data activities would fail entirely as required data elements could not be found and no common definition of sources of record were kept. Furthermore, the university's data integration toolset, primarily built around ETL processing, required broad skillsets and scarce resources to deploy, maintain, and manage. As a result, the development time needed for information access was long-so long, in fact, that by the time data was retrieved, it was often less useful or even irrelevant for decisions. In addition to the noted challenges of data and development timeliness, data security and privacy were also at risk within the traditional university reporting approach, as row-level access controls were integral only within the enterprise data warehouse (EDW). Other data sources and reporting environment offshoots (shadow systems) outside the EDW often lacked this same, fine-grained access control, thereby increasing the possibility of a compromise.

Indiana University (IU) is a multi-campus institution with 8 locations spread throughout Indiana. It serves a student body of more than 114,000 individuals and boasts more than 19,000 employees. Ranked 20th amongst public colleges by Forbes Magazine in 2016, Indiana University is also recognized as an “R1: Doctoral University – Highest Research Activity” by the Carnegie ClassificationTM and operates with an annual budget of $3.4B. Like most educational institutions, IU has had a long history in business reporting and business intelligence, dating back to the days of the mainframe. Recently, the university began a new, multi-year project called the Decision Support Initiative (DSI), dedicated to helping IU improve decision making through enhanced data, models, and processes. DSI aims to improve access to data and analytic technologies, thereby providing transparency across the IU system, leading to better-informed decision outcomes.

Responding to these historical challenges and preparing for the future, members of the DSI team focused on the creation of a single system of easily consumable information assets to meet the data needs of the university. Harnessing the power of data virtualization, IU chose the Denodo Platform to create a logical data warehouse (LDW). In this particular architecture, Denodo connects the university systems of record to data-consuming applications, providing heterogeneous data connectivity, delivery, security, and governance services. With Denodo, IU has successfully combined data sources such as Oracle, MS-SQL, Amazon Redshift, Web services and Box.com, securely serving information to consuming applications such as Tableau and Excel. Perhaps most importantly, the Denodo Platform vastly improves the university's security and compliance posture, providing fine-grained access control and auditing across data sources of many types. With Denodo, user management is simplified via active directory groups and SAML integrations, providing the right access to the right users at the right time.

• With the logical data warehouse in place, decision makers at Indiana University now have ready access to the data they need, when they need it.
• The Denodo Platform seamlessly delivers the information required to improve outcomes while requiring fewer technical resources, improving security, and enhancing agility when compared to its traditional data warehouse forerunner.
• In fact, the university is leveraging the Denodo Platform well beyond the LDW, satisfying data blending and access needs through use of Denodo java extensibility in new and inventive ways.

• Significantly improved information agility across the university.
• Diverse data spread across the entire enterprise can now be accessed securely with a proper authorization structure.
• Core Business Intelligence logic is becoming centralized, thus reducing duplication of effort and enhancing development efficiency.