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02 V3 IAB PORTRAIT SPECIFICATIONS & STYLE GUIDE IN CONTEXT AD UNIT PLACEMENT ADVERTISEMENT 1050 270 15 15 40 460 5 15 10 220 50 15 220 15 300 Area for Ad App 03 Area for Ad App 02 Area for Ad App 01 Area for Logo ADVERTISEMENT 03 IAB PORTRAIT SPECIFICATIONS & STYLE GUIDE DIMENSIONS BASE CONFIGURATION
2 #237635 ©2012 IDC SITUATION OVERVIEW The Real-Time Enterprise Challenge Enterprises are struggling to keep up with the demands of business in a globally, electronically connected world. Not only do events that require response come at an ever- quickening pace, but business intelligence (BI) about customers and competitors may be gleaned from vast amounts of ever-changing data on the Internet, if only it can be rapidly acquired and processed. Business managers know that their competitors are chasing this intelligence as fast as they are. How can a modern enterprise keep up with the pace of business demands and also gain an edge from timely business intelligence? The key is in the ability to acquire and ingest all the necessary data and to act on that data with as little delay as possible. This means dealing with streaming data from external sources and sensor and other machine-generated data from internal sources. It means adopting Big Data technologies to collect and ingest large amounts of business intelligence data quickly. Additionally, it means having a core data management platform that can enable applications to put all the pieces together and act in a timely manner. Memory-based database technology powering an IMDB needs to be at the heart of such a platform. What Is a Real-Time Enterprise? A real-time enterprise can act on events as they happen rather than wait for relevant information to be entered into the system, stored, compiled, and made available for query and reporting. A real-time enterprise needs to handle shifting external factors such as customer demand, supplier pricing and product availability, and operational costs as well as internal factors such as logistics, inventory, and production rates. This is not simply about producing an "executive dashboard." This is about marshalling IT resources based on the current situation on the ground as it changes. It is about automated decision generation and action and about supporting just-in- time tactical decisions. It affects both transactional operational systems and analytic systems, including operational BI. Big Data in Motion and at Rest Part of what drives the real-time enterprise is Big Data. Most people are familiar with Big Data at rest, which involves collecting large amounts of data that may be either streaming, machine-generated data or unorganized collections of content; filtering, ordering, and formatting that data; and making the data available to drive decisions and actions. Hadoop falls into this category, and most Big Data at rest solutions, including those based on Hadoop, are batch oriented or have a batch component to them. As a result, there is always a delay of minutes to hours from when the data arrives and when it is available to drive actions. For some classes of decisions and actions, this is fine; for others, not so much. Big Data in motion is different. This also involves large amounts of streaming data, but instead of ingesting the data and then examining it, this approach involves recognizing events in the data and taking immediate action. Such technology
WHITE PAPER In-Memory Database Technology: A Critical Success Factor for the Real-Time Enterprise Sponsored by: SAP Carl W. Olofson November 2012 IDC OPINION No one needs to be told that the pace of business for most enterprises is increasing
WHITE PAPER In-Memory Database Technology: A Critical Success Factor for the Real-Time Enterprise Sponsored by: SAP Carl W. Olofson November 2012 IDC OPINION No one needs to be told that the pace of business for most enterprises is increasing
