A Data Warehouse is a computer system designed for archiving and analyzing an organization's historical data, such as sales, salaries, or other information from day-to-day operations. Normally, an organization summarizes and copies information from its operational systems to the data warehouse on a regular schedule, such as every night or every weekend; after that, management can perform complex queries and analysis on the information without slowing down the operational systems.
BI systems have encapsulated a very waterfall-like approach, where a large amount of design work must be done by technology professionals up front, before even simple business analysis can be done. Join Gigaom Research and our sponsor SiSense for “BI Agility: A clear win, if done right,” a free analyst webinar on Wednesday, September 10, 2014 at 10 a.m. PT.
The Editor interviews Deidre Paknad, Vice President of IBM’s Information Lifecycle Governance (ILG) Solutions Business, former CEO of PSS Systems, and founder of the Compliance, Governance and Oversight Council (CGOC).
Today’s IT organizations face huge challenges such as the ever-increasing number of applications, virtualization, the cloud, and the rising value of information stored in data centers. The combined effect of these factors is placing pressure on IT infrastructures to increase performance and operate more efficiently while reducing costs.
An emerging technology, flash storage technology, is helping business and technology leaders address these issues by making their IT infrastructures more operationally efficient. Learn more in this white paper from Logicalis.
Join this session to understand how you can reduce the cost and complexity of backup and recovery while ensuring comprehensive data protection across virtual environments, core application and remote sites.
Following a series of in-depth interviews with Senior IT professionals in various industries this video provides their findings and the direct and in-direct value derived from using HPs Backup, Recovery and Archiving solutions.
Learn about the central issues that tend to be consistent across all Request for Proposals (RFPs) and see what questions you should be asking in order to maximize the efficiency of your mission critical data center.
Digitalization—the process of exploiting digital information to maximize business success—has increased the value of your data to the point where it is arguably your most important asset. This paper explains why mastery will not be possible with merely adequate integration technology.
This book examines data storage and management challenges and explains software-defined storage, an innovative solution for high-performance, cost-effective storage using the IBM General Parallel File System (GPFS).
From its conception, this special edition has had a simple goal: to help SAP customers better understand SAP HANA and determine how they can best leverage this transformative technology in their organization. Accordingly, we reached out to a variety of experts and authorities across the SAP ecosystem to provide a true 360-degree perspective on SAP HANA.
This TDWI Checklist Report presents requirements for analytic DBMSs with a focus on their use with big data. Along the way, the report also defines the many techniques and tool types involved. The requirements checklist and definitions can assist users who are currently evaluating analytic databases and/or developing strategies for big data analytics.
For years, experienced data warehousing (DW) consultants and analysts have advocated the need for a well thought-out architecture for designing and implementing large-scale DW environments. Since the creation of these DW architectures, there have been many technological advances making implementation faster, more scalable and better performing. This whitepaper explores these new advances and discusses how they have affected the development of DW environments.
New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose built platforms more capable of meeting the real-time needs of a more demanding end user and the opportunities presented by Big Data. Significant strategy shifts are under way to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support Big Data and real-time needs of innovative enterprises companies.
This white paper discusses the issues involved in the traditional practice of deploying transactional and analytic applications on separate platforms using separate databases. It analyzes the results from a user survey, conducted on SAP's behalf by IDC, that explores these issues.
This paper explores the results of a survey, fielded in April 2013, of 304 data managers and professionals, conducted by Unisphere Research, a division of Information Today Inc. It revealed a range of practical approaches that organizations of all types and sizes are adopting to manage and capitalize on the big data flowing through their enterprises.
In-memory technology—in which entire datasets are pre-loaded into a computer’s random access memory, alleviating the need for shuttling data between memory and disk storage every time a query is initiated—has actually been around for a number of years. However, with the onset of big data, as well as an insatiable thirst for analytics, the industry is taking a second look at this promising approach to speeding up data processing.
Over the course of several months in 2011, IDC conducted a research study to identify the opportunities and challenges to adoption of a new technology that changes the way in which traditional business solutions are implemented and used. The results of the study are presented in this white paper.
Forrester conducted in-depth surveys with 330 global BI decision-makers and found strong correlations between overall company success and adoption of innovative BI, analytics, and big data tools. In this paper, you will learn what separates the leading companies from the rest when it comes to exploiting innovative technologies in BI and analytics, and what steps you can take to either stay a leader or join their ranks.
This white paper, produced in collaboration with SAP, provides insight into executive perception of real-time business operations in North America. It is a companion paper to Real-time Business: Playing to win in the new global marketplace, published in May 2011, and to a series of papers on real-time business in Europe, Asia-Pacific and Latin America.
Leading companies and technology providers are rethinking the fundamental model of analytics, and the contours of a new paradigm are emerging. The new generation of analytics goes beyond Big Data (information that is too large and complex to manipulate without robust software), and the traditional narrow approach of analytics which was restricted to analysing customer and financial data collected from their interactions on social media. Today companies are embracing the social revolution, using real-time technologies to unlock deep insights about customers and others and enable better-informed decisions and richer collaboration in real-time.
Speed, simplicity and affordability: 3 capabilities businesses need from their warehousing environment. IBM DB2 with BLU Acceleration gives organizations a complete, multipurpose environment to rapidly distill insight from their data, make timely decisions and capitalize on opportunities