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Documents related to » owb data warehousing olap


Transactional Data: Driving Real-Time Business
A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business

owb data warehousing olap  Data: Driving Real-Time Business A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more. Read More...
Addressing the Complexities of Remote Data Protection
As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and

owb data warehousing olap  the Complexities of Remote Data Protection Because data protection is a concern for organizations of all sizes, IBM offers remote data protection for the enterprise, as well. This high performance and easy-to-use service delivers consistent and cost-effective data protection without increased network investment. Source: IBM Resources Related to Addressing the Complexities of Remote Data Protection : Continuous Data Protection (CDP) (Wikipedia) Addressing the Complexities of Remote Data Read More...
2012 Business Data Loss Survey results
This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download

owb data warehousing olap  Business Data Loss Survey results This report on the Cibecs and IDG Connect 2012 business data loss survey uncovers the latest statistics and trends around enterprise data protection. Download the full results now. Read More...
TCO Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center
Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30

owb data warehousing olap  Analysis of a Traditional Data Center vs. a Scalable, Containerized Data Center Standardized, scalable, pre-assembled, and integrated data center facility power and cooling modules provide a total cost of ownership (TCO) savings of 30% compared with traditional, built-out data center power and cooling infrastructure. Avoiding overbuilt capacity and scaling the design over time contributes to a significant percentage of the overall savings. This white paper provides a quantitative TCO analysis of the Read More...
The Data Explosion
RFID and wireless usage will drive up data transactions by ten fold over the next few years. It is likely that a significant readdressing of the infrastructure

owb data warehousing olap  Data Explosion Introduction Traffic on the World Wide Web continues to grow. Traffic on your S mall S mart F ast devices continues to grow. Ok, I admit it. I bought the cell phone that takes pictures. I didn''t know if it was useful; but being a technophile, I went for it. And rapidly it all came to me! I tried on a new cool jacket ... I crooned over it ... but for that much money, I wasn''t sure. Should I really buy this? Enter the pic in my cell phone! We chicks have our honor guard. You know those Read More...
An Improved Architecture for High-efficiency, High-density Data Centers
Globally, data center power and cooling infrastructure wastes more than 60 million megawatt-hours per year that do not contribute usefully to powering IT

owb data warehousing olap  humidification. By contrast, the rowbased CRAC has an efficiency of 95% at 70% IT load, which means that only 5% of the input power is going to fan and humidification. This is a factor of four reduction in loss. The above chart was developed assuming a chilled water design, tier 4 design, 3-foot raised floor for the room cooling solution, and an average power of 10kW per rack. This data is only for the CRAH unit and does not include the chiller, pumps, and cooling tower. These devices can be studied Read More...
Managing Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses
To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if

owb data warehousing olap  Small Data Centers: A Short Guide to Running Secure and Resilient Data Centers for Mid-sized Businesses To keep your growing business competitive, your data center must be secure, protected against disaster, and available 24 hours a day, 7 days a week. But if managing IT is not your core competence, what are your options? A managed service provider (MSP) can help. Learn about the benefits of outsourcing data center management, and make sure your crucial business applications are always available Read More...
The Value of Big Data
As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity

owb data warehousing olap  Value of Big Data As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value. Read More...
Six Steps to Manage Data Quality with SQL Server Integration Services
Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business

owb data warehousing olap  Steps to Manage Data Quality with SQL Server Integration Services Melissa Data''s Data Quality Suite operates like a data quality firewall '' instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Six Steps to Manage Data Quality with SQL Server Integration Services : Data quality (Wikipedia) Six Steps to Manage Data Quality with SQL Server Integration Services Data Quality is also known as : Read More...
Scalable Data Quality: A Seven-step Plan for Any Size Organization
Every record that fails to meet standards of quality can lead to lost revenue or unnecessary costs. A well-executed data quality initiative isn’t difficult, but

owb data warehousing olap  Data Quality: A Seven-step Plan for Any Size Organization Melissa Data’s Data Quality Suite operates like a data quality firewall – instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Scalable Data Quality: A Seven-step Plan for Any Size Organization : Data quality (Wikipedia) Scalable Data Quality: A Seven-step Plan for Any Size Organization Data Quality is also known as : Customer Read More...
Automate to Optimize: The Foundation for Data Center Efficiency
IT administrators need to simplify both complex and routine tasks to deliver increasing value with limited resources. Data center automation can help minimize

owb data warehousing olap  to Optimize: The Foundation for Data Center Efficiency Automate to Optimize : The Foundation for Data Center Efficiency If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Today’s heterogeneous enterprise data center environments are quickly growing in size and complexity, driven by mergers and acquisitions, expansion into multiple data centers, and large-scale initiatives such as server and storage consolidation. Source : Tidal S Read More...
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete

owb data warehousing olap  Center Projects: Advantages of Using a Reference Design It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and Read More...
Data Quality Basics
Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at

owb data warehousing olap  Quality Basics Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue. 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

owb data warehousing 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...
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.

owb data warehousing olap  in, 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 Read More...

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