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Software Functionality Revealed in Detail
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 data centric approach


CAD-centric PLM, ERP-centric PLM, and Organic PLM: What's Right for You? - Part 3
Part 1 of this blog series started with the assertion that product lifecycle management (PLM) solutions are becoming increasingly important to enterprises in a

data centric approach  means a compartmentalized  product data management (PDM)  implementation in an engineering department, with not many instituted collaborative PLM processes across other departments and trading partners. My post concluded that in spite of the elusive benefits from PLM collaboration, switching from one PLM system for another one (regardless of its CAD or ERP origin) in a rip-and-replace manner will not necessarily solve most of the aforementioned issues. Can the New Organic Crop of PLM Apps Help? But

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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

CRM for Financial and Insurance Markets

Customer relationship management (CRM) focuses on the retention of customers by collecting data from all customer interactions with a company from all access points (by phone, mail, or Web, or in the field). The company can then use this data for specific business purposes by taking a customer-centric rather than a product-centric approach. CRM applications are front-end tools designed to facilitate the capture, consolidation, analysis, and enterprise-wide dissemination of data from existing and potential customers. This process occurs throughout the marketing, sales, and service stages, with the objective of better understanding one’s customers and anticipating their interest in an enterprise’s products or services.  

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A Demand-driven Approach to BI


The core concept behind the Vanguard solution is that business intelligence (BI) must be demand-driven, which means that the business needs of the user dictate the technical solution, not the other way around. In other words, it should let the business users drive the process, and remove the problems of content relevance and software complexity.

data centric approach  by making the underlying data architecture transparent to the users, who have access to information from multiple systems, platforms, or locations, and view it in a functional user interface. To that end, Vanguard's Unified Information Model (UIM) ensures that the appropriate business rules are applied and the information appears in a consistent, integrated context (whereby the user environment allows business users to identify and retrieve exactly the information they need), and provides easy-to-use Read More

Sword Ciboodle-One More BPM-Centric CRM Provider


What does BPM have to do with CRM? Sword Ciboodle can tell you. The vendor delivers process-based customer interaction solutions to contact centers to improve the customer experience by improving customer-facing processes. TEC principal analyst P.J. Jakovljevic reviews the vendor’s key offerings and sits down with Ciboodle’s VP of product and market strategy to discuss the company’s challenges, strategies, and technologies.

data centric approach  , Capita , Dimension Data , eLoyalty , HiSoft , Revelant Technologies , and Solvis Consulting . The company’s telephony partners are Avaya, Cisco, and Genesys, and the product independent software vendor (ISV) partners are Radian6 (part of salesforce.com) for social monitoring, text analytics, and sentiment analysis, and SAS , whose Real Time Decision Manager has been integrated with Ciboodle One to provide a higher level of personalization to the customer. International delivery partners include CSC, Read More

CAD-centric PLM, ERP-centric PLM, and Organic PLM: What's Right for You? - Part 1


In this day and age of globalization, ever-shorter new product introduction (NPI) cycles and overall product lifecycles, partner collaboration, and whatnot, product lifecycle management (PLM) software solutions have lately increased their strategic significance to enterprises. In his recent Forbes blog post contribution, PTC’s CEO Jim Heppelmann touts PLM as a new path to shareholder value. He

data centric approach  the PLM repository of data should be an enterprise system of record rather than mundane transactional enterprise resource planning (ERP) data . With Apple recently leapfrogging its once seemingly untouchable competitors via innovation and delivery of cherished products as well as with the rebirth of General Motors (GM), Chrysler , and Ford via innovation and a departure from their former gas guzzlers with numerous quality issues, it is difficult to debate the importance of product development and its Read More

Microsoft's Dynamic New Approach to Professional Services Automation


In the short term, Microsoft Dynamics SL will likely follow the professional services automation (PSA) trend of extending functionality to the Web. In the long term, its eventual absorption into the Microsoft Dynamics product line may affect Microsoft's strategy in the project portfolio management marketplace.

data centric approach  Dynamics SL supports electronic data interchange (EDI) and e-commerce capabilities. Furthermore, this module has robust order management and purchasing features that are specific to distribution organizations. Foundation Microsoft Dynamics SL's Foundation module allows users to work with other Microsoft applications and technologies, as well as with Crystal Reports and the Business Portal . In addition, the Foundation module is delivered with a tool kit for customizations and integrations utilizing 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.

data centric approach  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 each step, Read More

Distilling Data: The Importance of Data Quality in Business Intelligence


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data centric approach  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 Read More

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 users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more.

data centric approach  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

Metagenix Reverse Engineers Data Into Information


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data centric approach  Reverse Engineers Data Into Information Metagenix Reverse Engineers Data Into Information M. Reed - February 15, 2001 Event Summary Metagenix, Inc. has designed its flagship product, MetaRecon to, as they put it, Decipher Your Data Genome . The product reverse engineers all of the metadata ( data about data ) from data sources and generates information that is very helpful to developers in designing specifications for a new data store, and assists greatly in preparing for cleansing and Read More

Data Quality Trends and Adoption


While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers.

data centric approach  of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers. Read More

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.

data centric approach  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 Read More

The Necessity of Data Warehousing


An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding technology selection and access to historical 'legacy' data are also discussed.

data centric approach  Necessity of Data Warehousing The Necessity of Data Warehousing M. Reed - August 2, 2000 Why the market is necessary Data warehousing is an integral part of the information age . Corporations have long known that some of the keys to their future success could be gleaned from their existing data, both current and historical. Until approximately 1990, many factors made it difficult, if not impossible, to extract this data and turn it into useful information. Some examples: Data storage peripherals such Read More

Business Basics: Unscrubbed Data Is Poisonous Data


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data centric approach  Basics: Unscrubbed Data Is Poisonous Data Introduction A manufacturing company experienced continually increasing overhead costs in its purchasing and materials departments. It also began to see increased inventory levels and production line delays. A consulting firm was brought in to analyze the company's materials management processes and the level of competence of its materials and procurement staff. After mapping the entire process, from the creation of a bill of materials through post-sales Read More

The Path to Healthy Data Governance


Many companies are finally treating their data with all the necessary data quality processes, but they also need to align their data with a more complex corporate view. A framework of policies concerning its management and usage will help exploit the data’s usefulness. TEC research analyst Jorge Garcia explains why for a data governance initiative to be successful, it must be understood as a key business driver, not merely a technological enhancement.

data centric approach  Path to Healthy Data Governance This article is based on the presentation, “From Data Quality to Data Governance,” by Jorge García, given at ComputerWorld Technology Insights in Toronto, Canada, on October 4, 2011. Modern organizations recognize that data volumes are increasing. More importantly, they have come to realize that the complexity of processing this data has also grown in exponential ways, and it’s still growing. Many companies are finally treating their data with all the necessary Read More