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Software Functionality Revealed in Detail
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 data quality processes


Distilling Data: The Importance of Data Quality in Business Intelligence
As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence

data quality processes  Data: The Importance of Data Quality in Business Intelligence Originally Published - October 20, 2008 The zeal to get as much business data to the user as soon as possible often prevails over the establishment of processes that control the quality of data. Low data quality standards can lead to bad business decisions and missed opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration

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Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

Compare Now

Core PLM for Discrete Industries

The foundation of product lifecycle management (PLM) for the discrete manufacturing industries is product data management (PDM). It covers design and product-related aspects of PLM including management of material specifications, product structures, production processes, design tools, document management, and design collaboration. 

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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 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.

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Business Basics: Unscrubbed Data Is Poisonous Data


Most business software system changes falter--if not fail--because of only a few root causes. Data quality is one of these root causes. The cost of high data quality is low, and the short- and long-term benefits are great.

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Getting Your Data, Processes & Procedures GFSI-Ready


Quality compliance required of food companies is changing, and tightening, in recent years. Many large customers are requiring that their suppliers certify to GFSI standards, and companies also face the daily barrage of internal quality procedures across production and warehousing areas, laboratories, carriers and third-party logistics providers. Know the quality management functionality that should be an integral part of your ERP system so you can meet your food quality compliance challenges.

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Using Data Analytics to Transform Your Business Processes and Your Business


Implementation of data-driven analytic platforms is quickly becoming the new business normal. New analytic tools are allowing organizations to improve the performance of routine tasks and procedures based on real-time, high-quality information, resulting in vastly improved operational and financial decision making. Dundas Data Visualization is a dashboard solution that can help your business increase compliance and improve efficiency by transforming raw data into visual information. Visualizing your organization’s data can give you a clearer understanding of what’s really happening in your organization, and help to identifying potential challenges. The adoption of Dundas Data Visualization dashboard solutions can help your business perform far above others in your field.

In this white paper, learn about what data analytics are, and how, in conjunction with up-to-the-minute information and access to great visualization tools, you can use them to your best business advantage. Dundas Data Visualization provides a detailed set of four key factors to help you develop better insight through advanced analytics: defining of business objectives, aligning stakeholders on business challenges, identifying meaningful metrics for better success, and putting insight to work by utilizing visual tools for more rapid understanding of concepts. Read tips on how to establish the definitions of success for your company through the development of a data discovery framework to harness the full potential of your data. Learn why it’s crucial to develop a system of support for and management of data analytics within your organization before adoption takes place, and why simply visualizing information can help with the adoption of new data analytics tools.

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Top 10 Evaluation Criteria for Copy Data Management & Data Virtualization


Data virtualization is becoming more important, as industry-leading companies learn that it delivers accelerated IT projects at a reduced cost. With such a dynamic space, one must make sure that vendors will deliver on their promises. This white paper outlines 5 qualification questions to ask before and during the proof of concept (POC), and 5 things to test during the POC.

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The Teradata Database and the Intelligent Expansion of the Data Warehouse


In 2002 Teradata launched the Teradata Active Enterprise Data Warehouse, becoming a key player in the data warehouse and business intelligence scene, a role that Teradata has maintained until now. Teradata mixes rigorous business and technical discipline with well-thought-out innovation in order to enable organizations to expand their analytical platforms and evolve their data initiatives. In this report TEC Senior BI analyst Jorge Garcia looks at the Teradata Data Warehouse in detail, including functionality, distinguishing characteristics, and Teradata's role in the competitive data warehouse space.

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Microsoft Azure Gets into Big Data and IoT


Microsoft has announced new and enhanced Microsoft data services related to handling big data (especially data streams) and the Internet of Things (IoT).

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Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

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Master Data Management and Accurate Data Matching


Have you ever received a call from your existing long-distance phone company asking you to switch to its service and wondered why they are calling? Chances are the integrity of its data is so poor that the company has no idea who many of its customers are. The fact is, many businesses suffer from this same problem. The solution: implement a master data management (MDM) system that uses an accurate data matching process.

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Linked Enterprise Data: Data at the heart of the company


The data silos of today's business information systems (IS) applications, and the pressure from the current economic climate, globalization, and the Internet make it critical for companies to learn how to manage and extract value from their data. Linked enterprise data (LED) combines the benefits of business intelligence (BI), master data management (MDM), service-oriented architecture (SOA), and search engines to create links among existing data, break down data walls, provide an open, secure, and long-term technological environment, and reduce complexity—read this white paper to find out how.

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