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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 main automation maturity levels

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 main automation maturity levels

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 main automation maturity levels  Review Automation Fundamentals | Data Main Automation Maturity Levels | Data Basic Level of Automation Maturity | Data Test Automation Maturity Efforts | Data Enterprise Continuous Integration Maturity Model | Data Scoring the Maturity of Organizations Automation | Data Release Automation Maturity Survey | Data Data Centre Automation | Data Test Management Automation | Data Advancing in Automation Maturity | Data Automation Maturity Model | Data Phase Brings Automation | Data Build Release Automation Read More

Expanding the Enterprise: Breaking the Barriers to Collaborative Product Development


Product development has never been easy, but in today’s global market, the pressures facing industrial manufacturers are even greater. With more stakeholders involved in the product development process, collaboration and communication are key to competitive advantage. Your challenge: bring all the stakeholders in the same room—in real time. Discover how to succeed by increasing innovation and speeding time-to-market.

data main automation maturity levels  practical reality. Technology- including data management, project management, or web-based collaboration tools - enables manufacturers to manage the entire lifecycle of a product, from its conception, through design and manufacture, to service and disposal. This extended product lifecycle, known as the Digital Product Value Chain, incorporates a variety of processes and supporting software systems. The two main components of the Digital Product Value Chain are Product Lifecycle Management (PLM) and Read More

A Leader in Service Management Tackles Multidimensional Growth


Founded in 1999, Servigistics, initially a service parts planning and optimization (SPP/O) specialist, has become a full-fledged service lifecycle management (SLM) platform. P.J. Jakovljevic, principal analyst at Technology Evaluation Centers (TEC), runs down the company's history of acquisitions and developments, and interviews Mark Vigoroso, Servigistics' senior vice president of global marketing and alliances.

data main automation maturity levels  and higher levels of data accuracy in the planning systems, reducing costs in safety stock and improving inventory control and visibility. It should also improve shop floor efficiencies, by providing access to historical diagnostics, troubleshooting, and repair techniques. With this visibility, field technicians will replace parts and deliver defective FRUs to a repair depot, thus maximizing the use of repairable parts and bolstering service margins. For their part, planners will have real-time Read More

Mobile Business Intelligence & Analytics


The convergence of business intelligence (BI) and mobility has been well under way for some time. As more professionals begin using smart phones and other mobile devices to keep up to date with business information, your company’s work force will start seeing mobile access to business data as the rule rather than the exception. Discover the benefits that are in store for an organization that embraces mobile analytics.

data main automation maturity levels  not to say that data security concerns should be ignored. However, having a BI platform with a comprehensive security infrastructure in place, this should not be an inhibitor. Rather the security provided should free a company to broaden the access it provides to its data. Understanding the reporting needs of each of the three main audiences of mobile BI, the executive, the sales and services team is critical. These needs will differ. Develop KPIs and reports that are meaningful to the user and content 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 main automation maturity levels  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

Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

data main automation maturity levels  Data Comes of Age: Shifting to a Real-time Data Platform New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a Read More

Aplicor


The Aplicor software solution is an integrated, wireless, and web-based CRM suite that includes sales force automation (SFA), marketing automation, project office, customer support, and an enterprise portal.  

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10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

data main automation maturity levels  Avoid When Building a Data Center Proper data center commissioning can help ensure the success of your data center design and build project. But it''s also a process that can go wrong in a number of different ways. In the white paper Ten Errors to Avoid when Commissioning a Data Center , find out which mistakes to avoid when you''re going through the data center commissioning process. From bringing in the commissioning agent too late into the process, to not identifying clear roles for commissioning team Read More

Protecting Critical Data


The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly.

data main automation maturity levels  Critical Data The first step in developing a tiered data storage strategy is to examine the types of information you store and the time required to restore the different data classes to full operation in the event of a disaster. Learn how in this white paper from Stonefly. Read More

Sales Force Automation (SFA) Buyer's Guide


The sales force automation buyer's guide will help you find the ideal sfa system for your company.

data main automation maturity levels  sales force automation sfa buyer guide,sales,force,automation,sfa,buyer,guide,force automation sfa buyer guide,sales automation sfa buyer guide,sales force sfa buyer guide,sales force automation buyer guide. Read More

Data Quality Basics


Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue.

data main automation maturity levels  Quality Basics Bad data threatens the usefulness of the information you have about your customers. Poor data quality undermines customer communication and whittles away at profit margins. It can also create useless information in the form of inaccurate reports and market analyses. As companies come to rely more and more on their automated systems, data quality becomes an increasingly serious business issue. Read More

Overall Approach to Data Quality ROI


Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI.

data main automation maturity levels  Approach to Data Quality ROI Data quality is an elusive subject that can defy measurement and yet be critical enough to derail any single IT project, strategic initiative, or even a company. Of the many benefits that can accrue from improving the data quality of an organization, companies must choose which to measure and how to get the return on investment (ROI)—in hard dollars. Read this paper to garner an overall approach to data quality ROI. Read More

Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

data main automation maturity levels  Blending for Dummies Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant. Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data Read More

Backing up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices


This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information technology (IT) infrastructure.

data main automation maturity levels  up Data in the Private Cloud: Meeting the Challenges of Remote Data Protection - Requirements and Best Practices This white paper describes some of the common challenges associated with protecting data on laptops and at home and remote offices and portrays proven solutions to the challenges of protecting distributed business data by establishing a private cloud/enterprise cloud. Learn which best practices can ensure business continuity throughout an organization with a distributed information Read More

Data Management and Analysis


From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As).

For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most accurate data tools and systems in place to efficiently carry out their daily tasks. Data generation development, data quality, document and content management, and data security management are all examples of data-related functions that provide information in a logical and precise manner.

data main automation maturity levels  perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users to data professionals—must have the most Read More