For many years, companies have been building data warehouses to analyze business activity and produce insights for decision makers to act on to improve business performance. These traditional analytical systems are often based on a classic pattern where data from multiple operational systems is captured, cleaned, transformed and integrated before loading it into a data warehouse. Typically, a history of business activity is built up over a number of years allowing organizations to use business intelligence (BI) tools to analyze, compare and report on business performance over time. In addition, subsets of this data are often extracted from data warehouses into data marts that have been optimized for more detailed multi-dimensional analysis.
Published By: Altiscale
Published Date: Oct 19, 2015
In this age of Big Data, enterprises are creating and acquiring more data than ever before. To handle the volume, variety, and velocity requirements associated with Big Data, Apache Hadoop and its thriving ecosystem of engines and tools have created a platform for the next generation of data management, operating at a scale that traditional data warehouses cannot match.
Business Intelligence (BI) has become a mandatory part of every enterprise’s decision-making fabric. Unfortunately in many cases, with this rise in popularity, came a significant and disturbing complexity. Many BI environments began to have a myriad of moving parts: data warehouses and data marts deployed on multiple platforms and technologies – each requiring significant effort to ensure performance and support for the various needs and skill sets of the business resources using the environment. These convoluted systems became hard to manage or enhance with new requirements. To remain viable and sustainable, they must be simplified.
Fortunately today, we have the ability to build simpler BI technical environments that still support the necessary business requirements but without the ensuing management complexity. This paper covers what is needed to simplify BI environments and the technologies that support this simplification.
Decision makers need data and they need it now. As the pace of business continues to accelerate, organizations are leaning heavily on data warehouses to deliver analytical grist for the mill of daily decisions. This Research Report from Aberdeen Group examines the benefits of data warehouse solutions that offer rapid information delivery while minimizing complexity for users and IT.
First generation warehouses were not designed to manage data at today's volume or variety. Coercing older technologies to satisfy new demands can be inefficient, burdensome and costly. Read how IBM PureData System for Analytics is built for simplicity and speed.
Today, there is unprecedented pressure on companies in all industry sectors to keep their supply chains running smoothly. This often means that these businesses with their ever-changing distribution channels and production centers feeding those supply chains, need to efficiently manage their warehouses. In this whitepaper, Business-software.com profiles the leading warehouse management software vendors.
Spatial data warehouses are becoming more common as government agencies, municipalities, utilities, telcos and other spatial data users start to share their data. This paper illustrates some of the issues that arise when undertaking data replication and data sharing.
Business Intelligence Software are applications that build on existing data warehouses and provide analytical processing tools that allow users to more effectively analyze such data. This, in turn, permits businesses to more rapidly develop existing and new analyses and reports for improved decision-making power and information dissemination capacity.
Clear Image was awarded a contract to supply and fit CCTV and Access control to NISA, one of the largest picking warehouses in Europe. The company runs 3 shifts per day and wanted to allocate lockers to employees. The simple solution would have been to give each employee a locker, but between Borer and Clear Image, a better solution was devised. Thanks to our technology, we can create one to many relationships between our devices.
In today’s competitive on-line world, the speed of change in customer behaviour is increasing. In addition, in industries such as retail banking, car insurance and to some extent retail, the Internet has become the dominant way in which customers interact with an organisation.
Yet in many data warehouses today, being able to analyse customer on-line behaviour is often not possible because the clickstream web log data needed to do this is missing. It is a key point because customer access to the web has made loyalty cheap.
A customer may store heavy file boxes in one of its warehouses, but Fireproof Records Center spends a lot of time strategizing about the paperless office. Based in Grove City, Ohio, the company helps businesses in central Ohio manage information more efficiently, offering a suite of cloud document management and scanning tools, including the easy-to-use Epson WorkForce® color document scanner.