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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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 data automation maturity


Evolution to Revolution: The Test Automation Maturity Curve
The evolution of test automation towards data-driven and key/action word frameworks reflects the realization that the process becomes more efficient if there is

data automation maturity  to Segmentation Autotester | Data Automation Maturity | Data Automation Processes | Data Marketing Automation Maturity Assessment | Data Evolution to Revolution Test Automation | Data Empiricism Theory Automation | Data Process Automation Technologies | Data Control and Automation Maturity | Data Correct Level of Automation | Data Integration Maturity Model | Data Automation Processes and Systems Maturity | Data Take Sample Automation Maturity | Data Review Automation Fundamentals | Data Main Automation

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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

Sales Force Automation (SFA)

Sales Force Automation (SFA) systems help sales and marketing teams with functions related to taking orders, generating proposals or quotes, managing territories, managing partners, and maintaining contact data. Systems often include various levels of analytic and reporting capabilities. 

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Documents related to » data automation maturity

Economic Benefits of PLM-enabled Collaboration


Many of today’s product lifecycle management (PLM)-enabling technologies allow complex information to be shared by dispersed teams of people. Product data management (PDM) technology is used to organize and provide access to your intellectual assets. PLM, its collaborative Product Definition management (cPDm) capabilities, and other solutions can help you go beyond asynchronous data sharing. Find out how.

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Professional Services Automation: Affordable Hosted Solutions for the Small to Medium Business Market


Although technology is pivotal in maintaining a competitive edge, many smaller professional services organizations (PSOs) have limited time and resources to dedicate to their IT infrastructure. For this reason, the application service provider model can be a very attractive offering.

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Business Process Management: How to Orchestrate Your Business


Business process management (BPM), having evolved over the past fifteen years, has finally reached a level of maturity where vendors are now abolishing functional silos to allow the enterprise-wide flow of business processes. It replaces the old, manual system of coordinating activities in a company and improves functionality and effectiveness through modeling, documentation, certification, collaboration, automation, and compliancy to minimize costly errors.

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The N-able MSP Maturity Model


A business' success delivering managed services depends on its ability to improve the delivery of effective and efficient services to its customer base. Learn about ways that managed services providers (MSPs) can develop a higher-value business by improving their ability to attract and retain high-quality customers and provide IT services in an effective manner.

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The Value of Big Data


As the use of big data grows, the need for data management will also grow. Many organizations already struggle to manage existing data. Big data adds complexity, which will only increase the challenge. This white paper looks at what big data is, the value of big data, and new data management capabilities and processes, required to capture the promised long-term value.

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Data Migration Management: A Methodology to Sustaining Data Integrity for Going Live and Beyond


For many new system deployments, data migration is one of the last priorities. Data migration is often viewed as simply transferring data between systems, yet the business impact can be significant and detrimental to business continuity when proper data management is not applied. By embracing the five phases of a data migration management methodology outlined in this paper, you can deliver a new system with quality data.

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Data Center Projects: Project Management


In data center design projects, flawed management frequently leads to delays, expense, and frustration. Effective project management requires well-defined responsibilities for every manager, tight coordination among suppliers, well-defined procedures for managing change, and consistent terminology. Learn how enforcing these requirements can help your company achieve an efficient process with a predictable outcome.

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Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

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The Operational Data Lake: Your On Ramp to Big Data


Companies recognize the need to integrate big data into their real-time analytics and operations, but this poses a lot of technical and resource challenges. Meanwhile, those organizations that have operational data stores (ODSs) in place find that, while useful, they are expensive to scale. The ODS gives real-time visibility into operational data. While more cost-effective than a data warehouse, it uses outdated scaling technology, and performance upgrades require very specialized hardware. Plus, ODSs just can't handle the volume of data that has become a matter of fact for businesses today.

This white paper discusses the concept of the operational data lake, and its potential as an on-ramp to big data by upgrading outdated ODSs. Companies that are building a use case for big data, or those considering an upgrade to their ODS, may benefit from this stepping stone. With a Hadoop relational database management system (RDBMS), companies can expand their big data practices at their own pace.

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Data Quality: A Survival Guide for Marketing


Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more.

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