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Software Functionality Revealed in Detail
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 data describes automation maturity

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.

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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 describes 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 less code to develop and maintain. Instead of taking twenty years to evolve towards efficiency, you can take a revolutionary leap with a code-free approach that makes it easier to implement, manage, and maintain automated tests.

data describes automation maturity  a Test Automation | Data Describes Automation Maturity | Data Datacenter Automation Accelerating | Data Program for Implementing Automation | Data Test Automation Maturity Strategy | Data Increasing Automation Maturity | Data Automation Maturity Example-based | Data Customer Requires Automation Testing | Data Automation of Thought Information Technology | Data Warehouse Automation Maturity | Data Warehouse Automation Project | Data Test Automation Strategic Evaluation | Data Automation Maturity Read More

Project Management Office: Framework Strategy


IT initiatives driven within silos, where each department maintain its own project management office, inhibits the overall cohesiveness and effectiveness of corporate strategy. This document outlines best practices to centralize and deliver a scalable and robust project management framework strategy.

data describes automation maturity  management training and a data repository for the timely and appropriate generation, collection, dissemination, storage, and ultimate disposition of project information. This can be achieved through the implementation of a centralized project management office (PMO), often referred to as the project management center of excellence (PM-COE). Strategic Report Overview The following sections describes a structured framework for the successful implementation of a PM-COE/PMO for internal technology groups to Read More

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.

data describes automation maturity  Patch Management | Remote Data Back-up | Technical Assistance | Time and Material Model | Price PER Desktop | IT Infrastructure | Outsourcing | RSP | Free Managed Service Provider | Master Managed Service Provider | Whitepaper for Managed Service Providers | What Means MSP | What is Managed Service Providers | IT Automation | Network Monitoring | Remote Control | Remote Desktop | Remote Management | System Management | Remote Support | Remote Assistance | Network Policy Enforcement | Asset Management | Read More

Microsoft Dynamics AX: The Chosen One Among Microsoft Dynamics ERP Equals? - Part 2


Part 1 of this blog series positioned all four Microsoft Dynamics enterprise resource planning (ERP) product lines and concluded that Microsoft Dynamics AX [evaluate this product] has been selected as the ace and global “platform” player in selected industries in the Dynamics ERP lineup. In other words, the product has been providing an industry-enabling layer upon which certified partners can

data describes automation maturity  was introduced, and XML data exchanges were supported through a set of  Web services  interfaces, the so-called Application Integration Framework (AIF) . Microsoft Dynamics AX 4.0 also introduced  Taskbar  navigation, increased international reach to 36 country localizations (including China, Brazil, and Japan), 40 languages, and full Unicode support, while the brand new Service Management module was a major functional enhancement. The Current State of Affairs The Microsoft Convergence 2008 Read More

Reporting Value of IT Services with Balanced Scorecards


A balanced scorecard is a measurement system for management that provides real insight into the status of a business or some part of it. Developed by Kaplan and Norton in the early 1990s, balanced scorecards provide a control system that helps ensure the right balance between different, and often times conflicting, perspectives. For example, an insurance company may increase profitability by offering incentives to claims assessors for taking a tough stance on payout, but will soon find dissatisfaction among its clients that may lead to lost business. Scorecards help ensure this balance and are an improvement over more traditional single dimension approaches that tend to be based purely on expense management and business growth.

data describes automation maturity  out irrelevant details, aggregate data to form a more meaningful view, display metrics on a digital dashboard, and alert users to potential problems and exceptions. At the end of the day, however, implementing a balanced scorecard boils down to two key tasks: What are the metrics AND how are they retrieved? The caveat, of course, is that strategy is inferred from the metrics and it is known what the strategy is. Getting the Right Metrics Process In an SLM scorecard, the internal process perspective shows Read More

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.

data describes automation maturity  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. Read More

Data Center Projects: Advantages of Using a Reference Design


It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are defined and their benefits are explained.

data describes automation maturity  aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and shorten the planning and implementation process and reduce downtime risks once up and running. In this paper reference designs are Read More

New Data Protection Strategies


One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets.

data describes automation maturity  Data Protection Strategies One of the greatest challenges facing organizations is the protection of corporate data. The issues complicating data protection are compounded by increased demand for data capacity and higher service levels. Often these demands are coupled with regulatory requirements and a shifting business environment. Learn about data protection strategies that can help organizations meet these demands while maintaining flat budgets. Read More

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.

data describes automation maturity  Success Factors to Cleansing Data Four Critical Success Factors to Cleansing Data If you receive errors when attempting to view this white paper, please install the latest version of Adobe Reader. Data Cleansing and Synchronization Services The pace with which companies are forced to operate and to compete globally has taxed exisitng systems and increased their inefficiencies. Source : PM ATLAS Business Group, LLC Resources Related to Critical Success Factors to Cleansing Data : Data Cleansing Read More

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.

data describes automation maturity  Data Integration: A Primer Originally published - August 22, 2006 Introduction Implementing a customer data management system can be the difference between success and failure in terms of leveraging an organization''s customer relationship management (CRM) system. Since customers drive profitability, organizations need a way to provide their employees with a single view of the customer and to provide that customer with above-average customer service. Unfortunately, this is not always the case. Read More

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.

data describes automation maturity  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 Read More

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.

data describes automation maturity  Steps to Manage Data Quality with SQL Server Integration Services Melissa Data''s Data Quality Suite operates like a data quality firewall '' instantly verifying, cleaning, and standardizing your contact data at point of entry, before it enters your database. Source : Melissa Data Resources Related to Six Steps to Manage Data Quality with SQL Server Integration Services : Data quality (Wikipedia) Six Steps to Manage Data Quality with SQL Server Integration Services Data Quality is also known as : Read More

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.

data describes automation maturity  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

Next-generation Data Auditing for Data Breach Protection and Risk Mitigation


Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system.

data describes automation maturity  generation Data Auditing for Data Breach Protection and Risk Mitigation Data breaches and leaks are on the rise—and the consequences, from theft of identity or intellectual property, can seriously compromise a company’s reputation. Stolen laptops, hacking, exposed e-mail, insider theft, and other causes of data loss can plague your company. How can you detect (and respond!) to breaches and protect your data center? Learn about the functions and benefits of an automated data auditing system. Read More

Types of Prefabricated Modular Data Centers


Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and compares their key attributes, and provides a framework for choosing the best approach(es) based on business requirements.

data describes automation maturity  of Prefabricated Modular Data Centers Data center systems or subsystems that are pre-assembled in a factory are often described with terms like prefabricated, containerized, modular, skid-based, pod-based, mobile, portable, self-contained, all-in-one, and more. There are, however, important distinctions between the various types of factory-built building blocks on the market. This paper proposes standard terminology for categorizing the types of prefabricated modular data centers, defines and Read More