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Documents related to » big data apache


Six Steps to Manage Data Quality with SQL Server Integration Services
Six Steps to Manage Data Quality with SQL Server Integration Services. Read IT Reports Associated with Data quality. Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in place, you can integrate data while improving its quality and facilitate a master data management application—at low cost.

BIG DATA APACHE: Six Steps to Manage Data Quality with SQL Server Integration Services Six Steps to Manage Data Quality with SQL Server Integration Services Source: Melissa Data Document Type: White Paper Description: Without data that is reliable, accurate, and updated, organizations can’t confidently distribute that data across the enterprise, leading to bad business decisions. Faulty data also hinders the successful integration of data from a variety of data sources. But with a sound data quality methodology in
9/9/2009 2:32:00 PM

Four Critical Success Factors to Cleansing Data
Four Critical Success Factors to Cleansing Data. Find Guides, Case Studies, and Other Resources Linked to Four Critical Success Factors to Cleansing Data. Quality data in the supply chain is essential in when information is automated and shared with internal and external customers. Dirty data is a huge impediment to businesses. In this article, learn about the four critical success factors to clean data: 1- scope, 2- team, 3- process, and 4- technology.

BIG DATA APACHE: easier. If not, no big deal, you just need to be aware that you will have some overhead for some behind the scenes technical tasks that are required in the process. Dirty data manifests itself in many different anomalies, below are just a few: Discrepancies in the structure of the data items and specified format Irregularities Integrity constraint violations Contradictions Duplicates Invalid Missing values (part or whole records) Orphaned data Examples of data anomalies: Multiple addresses for IBM Same
1/14/2006 9:29:00 AM

Oracle Database 11g for Data Warehousing and Business Intelligence
Oracle Database 11g for Data Warehousing and Business Intelligence. Find RFP Templates and Other Solutions to Define Your Project In Relation To Oracle Database, Data Warehousing and Business Intelligence. Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

BIG DATA APACHE: Oracle Database 11g for Data Warehousing and Business Intelligence Oracle Database 11g for Data Warehousing and Business Intelligence Source: Oracle Document Type: White Paper Description: Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can
4/20/2009 3:11:00 PM

Achieving a Successful Data Migration
Achieving a Successful Data Migration. Solutions and Other Software to Delineate Your System and for Achieving a Successful Data Migration. The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.

BIG DATA APACHE: Achieving a Successful Data Migration Achieving a Successful Data Migration Source: Informatica Document Type: White Paper Description: The data migration phase can consume up to 40 percent of the budget for an application implementation or upgrade. Without separate metrics for migration, data migration problems can lead an organization to judge the entire project a failure, with the conclusion that the new package or upgrade is faulty--when in fact, the problem lies in the data migration process.
10/27/2006 4:30:00 PM

Data Quality Strategy: A Step-by-step Approach
Success start with data quality strategy: a step-by-step approach.Read Technology Evaluation Centers (TEC) whitepapers. To realize the full benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it, and how to keep it clean. The companies that approach this issue strategically are the companies that will be successful. Learn the six factors that go into a good data quality strategy, and find out how to go from strategy to implementation.

BIG DATA APACHE: What are the three biggest challenges of implementing a business intelligence/data warehousing (BI/DW) project within your organization? Of the 688 people who responded, the number-one answer (35% of respondents) was budget constraints. Tied with budget constraints, the other number-one answer was data quality. In addition, an equal number of respondents (35%) cited data quality as more important than budget constraints. Put simply, to realize the full benefits of their investments in enterprise
1/25/2010 1:13:00 PM

The Modern Virtualized Data Center
Data center resources are often underused while drawing enormous amounts of power and taking up valuable floor space. Virtualization has been a positive evolutionary step in the data center, driving consolidation of resources to maximize power saving and to simplify management and maintenance. Learn more about the benefits of virtualization, and the issues you need to consider when planning a consolidation project.

BIG DATA APACHE: The Modern Virtualized Data Center The Modern Virtualized Data Center Source: Pillar Data Systems Document Type: White Paper Description: Data center resources are often underused while drawing enormous amounts of power and taking up valuable floor space. Virtualization has been a positive evolutionary step in the data center, driving consolidation of resources to maximize power saving and to simplify management and maintenance. Learn more about the benefits of virtualization, and the issues you need to
8/15/2008 2:38:00 PM

Data Center Automation
With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response to market demands.

BIG DATA APACHE: Data Center Automation Data Center Automation Source: Quocirca Ltd Document Type: White Paper Description: With the increasing complexity of the data center and its dependent systems, data center automation (DCA) is becoming a necessity. To replace the costly and inefficient human aspect of managing the data center, IT departments must adopt DCA solutions. Combined with utility-based computing architectures, these solutions can provide greater dynamics in the environment and facilitate speed of response
10/30/2007 6:19:00 PM

5 Keys to Automated Data Interchange
5 Keys to Automated Data Interchange. Find Out Information on Automated Data Interchange. The number of mid-market manufacturers and other businesses using electronic data interchange (EDI) is expanding—and with it, the need to integrate EDI data with in-house enterprise resource planning (ERP) and accounting systems. Unfortunately, over 80 percent of data integration projects fail. Don’t let your company join that statistic. Learn about five key steps to buying and implementing EDI to ERP integration software.

BIG DATA APACHE: to work with the big guys right? The right answer is going to depend on the market focus of your EDI integration software vendor. Do they primarily focus on enterprise customers? If that s their main area of focus, how much attention will you be able to get as a midmarket organization? Will you be on the top of the priority list if there are any problems? Are you going to get access to the best resources the vendor has available? Select a data integration vendor that focuses on small and mid-market
3/26/2008 3:35:00 PM

The New Virtual Data Centre
Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward.

BIG DATA APACHE: New Face of Engagement Big Data, Mobility, and Green IT: Innovations for Manufacturers and Distributors Tying the Shop Floor to the ERP System ERP Industry Consolidation: A New Trend or an Ongoing Process? Acronym-Related White Papers: Business Intelligence (BI) |  Customer Relationship Management (CRM) |  Enterprise Resource Planning (ERP) |  Human Capital Management (HCM) |  Information Technology (IT) |  Key Performance Indicators (KPIs) |  Return on Investment (ROI) |  Software as a Service
2/3/2011 8:58:00 AM

Actian Goes Big on Data, Acquires ParAccel » The TEC Blog
repositioning itself within the big data and data management space. It has just made an interesting move towards strongly increasing its presence by acquiring ParAccel , a provider of one of the fastest analytic databases on the market. This is a major second step for Actian after having acquired  Pervasive Software , a well-known predictive analytics and data integration company. With the  ParAccel acquisition, Actian is automatically putting in its pocket some very significant partners and custome

BIG DATA APACHE: actian, analytics, big data, big data analytics, Business Intelligence, Cloud Computing, data management, data warehouse, paraccel, pervasive, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
26-04-2013

Data Quality Strategy: A Step-by-Step Approach
To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

BIG DATA APACHE: Data Quality Strategy: A Step-by-Step Approach Data Quality Strategy: A Step-by-Step Approach Source: SAP Document Type: White Paper Description: To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP
3/16/2011 2:03:00 PM


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