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Documents related to » high profile data losses


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.

HIGH PROFILE DATA LOSSES: relevant marketing to a high value customer. Supporting MDM Along with setting up a Total Data Quality solution, you will need to deal with the other challenge of MDM — mainly, the deduplication of data from disparate sources with the integration provided by SSIS. An MDM application that combines data from multiple data sources might hit a roadblock merging the data if there isn t a unique identifier that is shared across the enterprise. This typically occurs when each data source system (i.e. an
9/9/2009 2:32:00 PM

Profile: Sbemco
Located in Algona, Iowa (US), and founded in 1989, Sbemco is a world leader in custom safety floor matting. As business grew, however, the company needed to strengthen back-office systems to provide more visibility into the supply chain process. The company accomplished this by transitioning to Exact Macola ERP and integrating it with Exact e-Synergy, a web-based business management solution.

HIGH PROFILE DATA LOSSES:
9/18/2006 3:21:00 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.

HIGH PROFILE DATA LOSSES: of the field is high, then add more analysis time up front. Mass Cleaning - This is a larger scale, more integrated process and requires about 30% to 50% involvement of the Data Project Team and 100% of the Data Cleansing Team. The concept here is to schedule workshops for each group of related fields/same business owners, analyze data and identify known/approved values as a team. Functional BA documents the data and business rules for that group of fields Functional BA sends the documentation to users
1/14/2006 9:29:00 AM

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.

HIGH PROFILE DATA LOSSES: : Data Migration , High Speed Data Migration , Data Migration Tool , Data Tape Recovery , Data Migration Strategies , Migrate Data Cost-Efficiently , Data Migration Guide , Process of Transferring Data , Data Migration Solutions , Data Migration Projects , Data Migration Professional Resource , Term Data Migration , Data Migration Pro , Data Migration Manager , Data Migration Steps , Data Migration Process , Data Migration Testing , Data Migration Plan , Migration Information Source , Transfers Database
10/27/2006 4:30:00 PM

The Why of Data Collection
Data collection systems work; however, they require a investment in technology. Before the investment can be justified, we need to understand why a data collection system may be preferable to people with clipboards.

HIGH PROFILE DATA LOSSES: objectives like lower inventory, higher quality, better customer service, or more accurate costing. We can often meet these objectives without a data collection system. For example, we can have people writing data on clipboards and later keying it in. Our data collection question is Will the results of using automated data collection be better than they were when we used people with clipboards? A frequent motivator for data collection systems is visibility. Simply put, we want to know more, and know it
11/3/2005

Data Discovery Applications » The TEC Blog
information. Some of the highlights among the functionalities that data discovery applications offer include the following: Easy-to-deploy data integration capabilities Exploration capabilities of both structured and unstructured data Rich drill-through capabilities Easy and powerful visual data modeling and visualization tools Features for enabling data mash-ups Rich enterprise data and content search capabilities Text enrichment and analysis features such as sentiment analysis Team collaboration

HIGH PROFILE DATA LOSSES: analytics, bi, Business Intelligence, Cognos Insight, data discovery, data discovery applications, endeca, Inetsoft, Lyza, PowerPivot, QlikView, style intelligence, Tableau, TIBCO spotfire, visual intelligence, webfocus visual discovery, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
17-08-2012

Massive Data Requires Massive Measures
There’s a lot of “big” money to be made these days when it comes to the analysis of big data. Find out what the key components are in this special report. One thing we learned in the data warehouse and data management world is that when it comes to the analysis of big data, there is also a lot of big money involved in order to gain position. But is the analysis of extensive amounts of data really a key component for the corporate business world?

HIGH PROFILE DATA LOSSES: of war was very high even in ancient times. It comes to no surprise that the ongoing war for increased presence in the data warehouse and information management space is — likewise — by no means cheap. In the corporate world, the information explosion has made it difficult for big organizations to collect, clean, store, and analyze such volumes of information. This has to do not only with quantity, but also with the number of sources, quality requirements, and the speed at which data is generated.
11/5/2010 10:03:00 AM

Best Practices for a Data Warehouse on Oracle Database 11g
Best Practices for a Data Warehouse on Oracle Database 11g. Find Out Software and Other Solutions for Your Decision Associated with Best Practices and Data Warehouse Management. Companies are recognizing the value of an enterprise data warehouse (EDW) that provides a single 360-degree view of the business. But to ensure that your EDW performs and scales well, you need to get three things right: the hardware configuration, the data model, and the data loading process. Learn how designing these three things correctly can help you scale your EDW without constantly tuning or tweaking the system.

HIGH PROFILE DATA LOSSES: typical to see a high CPU utilization and/or significant user IO waits. Figure 19 shows an Oracle Enterprise Manager Database Control screenshot of the performance page focused on the graph with wait events. The parallel execution workload shows a lot of IO waits and not a very high CPU utilization on this system. If you were to look at an AWR or statspack report for the same time period as shown in Figure 19 it is likely you would see PX wait events on the top or near the top of the wait event list. The
4/20/2009 3:11:00 PM

Vitria OI 4: Data for Today and for the Future » The TEC Blog
analyzing data at a high speed, at a time when technologies for this purpose abound. And as larger volumes of information are currently being generated and consumed, software vendors are challenged to provide the technology that enables users to gain insights from multiple sources of information. Vitria’s new OI 4 version includes important new capabilities to deal with the so-called big data sources, expanding the reach of data collection and processing to those data silos residing in the big data

HIGH PROFILE DATA LOSSES: BPM, Business Intelligence, operational intelligence, vitria, vitria operational intelligence suite, TEC, Technology Evaluation, Technology Evaluation Centers, Technology Evaluation Centers Inc., blog, analyst, enterprise software, decision support.
27-08-2013

How Healthy Is Your Data Center?
IT pros managing hospital data centers with mixed network environments, long lists of remote access protocols and applications, multiple user interfaces, and what often feels like way too many tools, are searching for remote access management solutions that are efficient, secure, and cost-effective to deploy. Learn which criteria to use as a benchmark when choosing a remote access solution for a health care environment.

HIGH PROFILE DATA LOSSES: data center, remote management, remote access, IT Infrastructure, Healthcare IT, CIO, CTO, DCIM.
10/10/2011 4:04:00 AM

Customer Data Integration: A Primer
Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

HIGH PROFILE DATA LOSSES: if these systems have high interoperability, many times the business rules and data structures of each application and business unit have not been taken into account, as they were developed independently of one another. This means that data may be captured in different ways. For example, customer address information and name may be recorded in different formats within different business units. When data is pulled from one system to another, this particular customer information may not be synchronized.
9/11/2009


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