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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 empiricism theory automation

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 empiricism theory automation

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 empiricism theory automation  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 Maturity Levels | Data Basic Level of Automation Maturity | Data Test Automation Maturity Efforts | Data Enterprise Continuous Integration Maturity Read More

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

data empiricism theory automation  Evolution of a Real-time Data Warehouse The Evolution of a Real-time Data Warehouse Jorge Garcia - December 23, 2009 Understanding Real-time Systems Today, real time computing is everywhere, from customer information control systems (CICSs) to real-time data warehouse systems. Real-time systems have the ability to respond to user actions in a very short period of time. This computing behavior gives real-time systems special features such as instant interaction: users request information from the system Read More

Unified Data Management: A Collaboration of Data Disciplines and Business Strategies


In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts.

data empiricism theory automation  Data Management: A Collaboration of Data Disciplines and Business Strategies In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts. Read More

Data Loss Prevention Best Practices: Managing Sensitive Data in the Enterprise


While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help.

data empiricism theory automation  Best Practices: Managing Sensitive Data in the Enterprise While a great deal of attention has been given to protecting companies’ electronic assets from outside threats, organizations must now turn their attention to an equally dangerous situation: data loss from the inside. Given today’s strict regulatory standards, data loss prevention (DLP) has become one of the most critical issues facing executives. Fortunately, effective technical solutions are now available that can help. 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 empiricism theory automation  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

Big Data: Operationalizing the Buzz


Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more.

data empiricism theory automation  the Buzz Integrating big data initiatives into the fabric of everyday business operations is growing in importance. The types of projects being implemented overwhelmingly favor operational analytics. Operational analytics workloads are the integration of advanced analytics such as customer segmentation, predictive analytics, and graph analysis into operational workflows to provide real-time enhancements to business processes. Read this report to learn more. Read More

Meet PCI DSS Compliance Requirements for Test Data with Data Masking


Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more.

data empiricism theory automation  Compliance Requirements for Test Data with Data Masking Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more. Read More

Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more agile architectures that can confront the new challenges much easier.

data empiricism theory automation  think Data Integration: Delivering Agile BI Systems with Data Virtualization Today’s business intelligence (BI) systems have to change, because they’re confronted with new technological developments and new business requirements, such as productivity improvement and systems as well as data in the cloud. This white paper describes a lean form of on-demand data integration technology called data virtualization, and shows you how deploying data virtualization results in BI systems with simpler and more Read More

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.

data empiricism theory automation  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. Read More

Operationalizing the Buzz: Big Data 2013


The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use to explore why and how companies are utilizing Big Data. Download the report and get all the results.

data empiricism theory automation  the Buzz: Big Data 2013 The world of Big Data is maturing at a dramatic pace and supporting many of the project activities, information users and financial sponsors that were once the domain of traditional structured data management projects. Research conducted by Enterprise Management Associates (EMA) and 9sight Consulting makes a clear case for the maturation of Big Data as a critical approach for innovative companies. The survey went beyond simple questions of strategy, adoption, and use 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 empiricism theory automation  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

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 empiricism theory automation  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

Data Pro Accounting Software


Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX.

data empiricism theory automation  Pro Accounting Software Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX. Read More

The Path to Healthy Data Governance through Data Security


Companies today are challenged to maintain their data safe and secure from hackers and others with unauthorized access. In his article, TEC business intelligence (BI) analyst Jorge García looks the risks and issues that companies face with securing their data, the importance and advantages of data security, and outlines a path that companies can follow to achieve data security as part of an overall data governance initiative.

data empiricism theory automation  Path to Healthy Data Governance through Data Security The appropriate handling of an organization’s data is critically dependent on a number of factors, including data quality, which I covered in one of my earlier posts this year. Another important aspect of data governance regards the managing of data from a security perspective. Now more than ever, securing information is crucial for any organization. This article is devoted to providing insight and outlining the steps that will put you on the path Read More

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.

data empiricism theory automation  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. Read More