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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.
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 using qlikview as data warehouse


Are Data Warehouses as Dead as the Dodo? (LiveDashBoard and QlikView)
If you think you have seen everything in the BI space, I’m sorry, but you may be wrong. Traditional BI solutions for large enterprises consider the data

using qlikview as data warehouse  these two BI products using the TEC Advisor . The initiatives of these two innovative BI vendors raise the following question: {democracy:43}

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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

Warehouse Management Systems (WMS)

A warehouse management system (WMS) should provide database and user-level tools in order for a company to optimize its storage facilities while at the same time providing user level task direction and activity support. The WMS should enable warehouse operators to optimize pick, put-away, and replenishment functions by employing powerful system logic to select the best locations and sequences. 

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Documents related to » using qlikview as data warehouse

SAP HANA-One Technology to Watch in 2012 (and Beyond)


Did you know that SAP HANA is much more than a high-speed analytic appliance? TEC principal analyst P.J. Jakovljevic reveals how HANA is a universal database that will enable companies to analyze large volumes of operational and transactional information in real time, from virtually any data source, and that will eventually deliver an entirely new class of applications that will change the way people think, work, plan, and operate.

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Are Data Warehouses as Dead as the Dodo? (Part 2: 1010data and Illuminate)


Although information analysis continues to be vital for insights into a company’s health and future, the traditional data warehouse structure may already be past its best-before date, due to major and radical transformations in the market. It may just be a matter of “Evolve or Die”. . . Indeed, in my last blog post Are Data Warehouses as Dead as the Dodo? (LiveDashBoard and QlikView)

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In-Memory Analytics: A Multi-Dimensional Study


The primary bottleneck to high-performance multidimensional analysis has been slow hard drive speed—the time it takes for data to be transferred from disk storage to random access memory (RAM). With crashing RAM prices and 64-bit addressing, in-memory architecture provides new and innovative solutions for online analytical processing (OLAP). This article looks at why and how in-memory technology transforms analytic applications for BI.

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Role of In-memory Analytics in Big Data Analysis


Organizations today need to handle and manage increasingly large volumes of data in various formats and coming from disparate sources. Though the benefits to be gained from analysis of such big data are immense, so are the inherent challenges, including need for rapid analysis. In his article, TEC BI analyst Jorge García discusses how in-memory analytics helps address these challenges and reap the benefits hidden in big data.

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Data Storage in the Cloud--Can You Afford Not To?


In Data Storage in the Cloud Can You Afford Not To?

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Is Selling Software in China Really as Hard as It Seems?


You’re a North American software vendor. You’re considering setting up shop in China.  You know that the risks are formidable, but so are the potential rewards. Among the risks: intellectual property piracy issues, cultural adaptation challenges, currency restrictions, and governmental censorship (see The cost of doing business in China: Privacy for an excellent post on the Chinese

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Demystifying Data Science as a Service (DaaS)


With advancements in technology, data science capability and competence is becoming a minimum entry requirement in areas which have not traditionally been thought of as data-focused industries. As more companies perceive the significance of real-time data capture and analysis, data as a service will become the next big thing. India is now the third largest internet user after China and the U.S., and the Indian economy has been growing rapidly. Read this white paper to find out more about how data SaaS is set to become a vital part of business intelligence and analytics, and how India will play a role in this trend.

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Agile Data Masking: Mitigate the Threat of Data Loss Prevention


You may not be as protected from data loss as you think. This infographic looks at some ways in which an enterprise's data can be compromised and vulnerable to security breaches and data loss, and shows how data masking can mean lower security risk and increased defense against data leaks.

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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 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.

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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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