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Documents related to » data warehousing analysis olap


Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio
Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the

data warehousing analysis olap  Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the Read More...
Customer Relationship Analysis Firm Extends Reach
thinkAnalytics signs a partnering agreement with one of the largest information technology services companies in North America. Why does CGI expect

data warehousing analysis olap  relational databases and for data mining. They became skilled at working with masses of data and embedding data analysis into traditional applications. Purchased by Gentia Software, an OLAP (On-Line Analytical Processing) specialist, in 1998; thinkAnalytics was recently launched as a separate company. The company''s product suite comprises a variety of analytic tools that sit on top of common middleware and analysis functions. The middleware functions do not replace traditional ETL Read More...
A One-stop Event for Business Intelligence and Data Warehousing Information
The Data Warehousing Institute (TDWI) hosts quarterly World Conferences to help organizations involved in data warehousing, business intelligence, and

data warehousing analysis olap  for Business Intelligence and Data Warehousing Information The Data Warehousing Institute ( TDWI ) hosts its quarterly World Conference in cities across the US to help organizations involved in data warehousing, business intelligence (BI), and performance management, by giving them access to industry experts, and providing impartial classes related to topics pertinent to the industry. As the industry grows, organizations are faced with questions about how to best access their data to drive profits and Read More...
A Definition of Data Warehousing
There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing

data warehousing analysis olap  Definition of Data Warehousing Biographical Information Bill Inmon Bill Inmon is universally recognized as the father of the data warehouse. He has over 26 years of database technology management experience and data warehouse design expertise, and has published 36 books and more than 350 articles in major computer journals. His books have been translated into nine languages. He is known globally for his seminars on developing data warehouses and has been a keynote speaker for every major computing Read More...
Microsoft Goes Their Own Way with Data Warehousing Alliance 2000
Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 vendors throughout the industry have qualified for Microsoft« Data

data warehousing analysis olap  Their Own Way with Data Warehousing Alliance 2000 Event Summary REDMOND, Wash., Nov. 30 /PRNewswire/ -- Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 top vendors throughout the industry have qualified for Microsoft Data Warehousing Alliance 2000. Alliance members and partners are committed to delivering tools and applications based on the Microsoft Data Warehousing Framework 2000, an open architecture for building business intelligence and analytical applications Read More...
Garbage in, Garbage out: Getting Good Data out of Your BI Systems
Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems.

data warehousing analysis olap  Garbage out: Getting Good Data out of Your BI Systems Garbage in, garbage out. Poor quality data leads to bad business decisions. You need high quality data in your business intelligence (BI) system to facilitate effective analysis—to make the right decisions at the right time. But how do you achieve this? Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems . In this Focus Brief , you''ll learn about the steps in the data delivery cycle, the problems can occur at each step, Read More...
Got Big Data? Net Big Dollars!
Data is growing at unprecedented rates. Data on customers, producers, underwriting, claims, and service providers is just part of the picture. This increase is

data warehousing analysis olap  Data? Net Big Dollars! Data is growing at unprecedented rates. Data on customers, producers, underwriting, claims, and service providers is just part of the picture. This increase is being driven by social media and mobile devices adding text and other nonstructured, as well as structured, data. Read this report to find out about the tremendous payback that comes from managing huge repositories of data. Read More...
Don''t Be Overwhelmed by Big Data
Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect

data warehousing analysis olap  Be Overwhelmed by Big Data Big Data. The consumer packaged goods (CPG) industry is abuzz with those two words. And while it’s understandable that the CPG world is excited by the prospect of more data that can be used to better understand the who, what, why, and when of consumer purchasing behavior, it’s critical CPG organizations pause and ask themselves, “Are we providing retail and executive team members with “quality” data, and is the data getting to the right people at the right time? Big Read More...
Effective Inventory Analysis: the 5 Key Measurements
The white paper effective inventory analysis isolates and walks you through five simple measurements that will help you ensure you are maximizing t...

data warehousing analysis olap  effective inventory analysis key measurements,effective,inventory,analysis,key,measurements,inventory analysis key measurements,effective analysis key measurements,effective inventory key measurements,effective inventory analysis measurements,effective inventory analysis key. Read More...
The Data Warehouse RFP
If you don’t have a data warehouse, you’re probably considering drafting a request for proposal (RFP) to screen vendors and ensure that your receive

data warehousing analysis olap  Data Warehouse RFP If you don’t have a data warehouse, you’re probably considering drafting a request for proposal (RFP) to screen vendors and ensure that your receive satisfactory information about the features of various hardware and software and their price. Writing an effective RFP that is well structured and includes different metrics will ensure that you receive the information you need and will make you look good. Read More...
Data Masking: Strengthening Data Privacy and Security
Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating

data warehousing analysis olap  Masking: Strengthening Data Privacy and Security Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you. Read More...
Protecting Critical Data
The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data

data warehousing analysis olap  Critical Data The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly. Read More...
Overall Approach to Data Quality ROI
Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company

data warehousing analysis olap  Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. Read More...
How to Comply with Data Security Regulations
A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation@and can be compliant with the common

data warehousing analysis olap  to Comply with Data Security Regulations BizDomainStore.com''s Remote Data Backups is the most cost effective, secure, and convenient way to automatically back up your mission critical data Source: BizDomainStore.com Resources Related to How to Comply with Data Security Regulations : Data Security (Wikipedia) How to Comply with Data Security Regulations Data security is also known as : Remote Data , Federal Data , State Data , Most Data , Mirrored Data , Financial Data , Client Data , Enterprise Data Read More...
Big Data Analytics: Profiling the Use of Analytical Platforms in User Organizations
While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as

data warehousing analysis olap  Data Analytics: Profiling the Use of Analytical Platforms in User Organizations While terabytes used to be synonymous with big data warehouses, now it’s petabytes, and the rate of growth in data volumes continues to escalate as organizations seek to store and analyze greater levels of transaction details, as well as Web- and machine-generated data, to gain a better understanding of customer behavior and drivers. This report examines the rise of big data and the use of analytics to mine that data. Read More...

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