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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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 bizdomain online data

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

Quote-to-Order RFI/RFP Template

Online Catalog, PIM Capabilities, Q2O/CPQ Workflow Management, Personalization and Localization, Rule Engines and Knowledge Base (Repository),Document Management (for Proposals and Contracts), Pricing, Customer Information, Reporting and Analysis, Integration and Interfacing Requirements, Engineering Capabilities, Channel Support and PRM, Aftermarket Services, and more. 

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Documents related to » bizdomain online data

How to Comply with Data Security Regulations


A remote data backup solution can be compliant with almost any international, federal, or state data protection regulation—and can be compliant with the common caveats of most data security laws by providing functionality like data encryption and secure media control. And, as some regulations require files to be archived for several years, you can create a routine that archives files you select for backup and storage.

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External Drive Backup Warning


Backing up critical data on an external drive provides only minimal protection against one type of data loss: hard drive failure and nothing else. External drives are easily damaged, lost, or stolen. Portable drive backups are rarely taken off-site and are insecure, time-consuming, and limited. And when an external drive holding key data no longer works, what will you do? There’s a better way to back up data. Learn more.

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Data Security Is Less Expensive than Your Next Liability Lawsuit: Best Practices in Application Data Security


Insecure data. Heavy fines due to non-compliance. Loss of customers and reputation. It adds up to a nightmare scenario that businesses want to avoid at all costs. However, this nightmare is preventable: knowledge base-driven data security solutions can be critical tools for enterprises wanting to secure not only their data—but also their status in the marketplace.

bizdomain online data   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.

bizdomain online data  data,data cleansing,consumer data,precise data cleansing,data quality,data cleansing tools,data cleansing solutions,accurate data,source data,data warehousing,data scrubbing,outsource data cleansing,data bureau services Read More

A Road Map to Data Migration Success


Many significant business initiatives and large IT projects depend upon a successful data migration. But when migrated data is transformed for new uses, project teams encounter some very specific management and technical challenges. Minimizing the risk of these tricky migrations requires effective planning and scoping. Read up on the issues unique to data migration projects, and find out how to best approach them.

bizdomain online data  Road Map to Data Migration Success Our consultants can help you optimize your end-to-end data migration by combining our expertise with our SAP BusinessObjects software to integrate your data and improve the data’s quality, particularly when upgrading or replacing legacy systems with SAP ERP. Source: SAP Resources Related to A Road Map to Data Migration Success : Data Migration (Wikipedia) A Road Map to Data Migration Success Data Migration Project is also known as : Road Map Data Migration Success 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.

bizdomain online data  data blending, data analyst, data source, data analysis, data software, data cleansing, data access, data blending software 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.

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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.

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Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

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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.

bizdomain online data  data science, big data, analytics, data SaaS, data scientist, India, data as a service, real-time data, data analytics Read More

Streaming Data and the Fast Data Stack


Big data is data at rest; fast data is streaming data, or data in motion. A stack is emerging across verticals and industries for building applications that process these high velocity streams of data. This new stack, the fast data stack, has a unique purpose: to grab real-time data and output recommendations, decisions, and analyses in milliseconds.

This white paper will look at the emerging fast data stack through the lens of streaming data to provide architects, CTOs, and developers with fundamental architectural elements of the new fast data stack: a LAMP stack for streaming data applications.

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Data Quality Strategy: A Step-by-Step Approach


To realize the benefits of their investments in enterprise computing systems, organizations must have a detailed understanding of the quality of their data—how to clean it and how to keep it clean. Those organizations that approach this issue strategically will be successful. But what goes into a data quality strategy? This paper from Business Objects, an SAP company, explores the strategy in the context of data quality.

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Data Warehouse vs. Data Mart-Approaches to Implementing a Data Integration Solution


There continues to be a wide variety of different approaches to building a solid data management solution for your organization, and just as many consulting firms across the globe willing to help you build them. However, it’s imperative for each data management solution to specialize to the unique needs of your organization’s business users, across varying functional areas.

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Data Masking: Strengthening Data Privacy and Security


Many business activities require access to real production data, but there are just as many that don’t. Data masking secures enterprise data by eliminating sensitive information, while maintaining data realism and integrity. Many Fortune 500 companies have already integrated data masking technology into their payment card industry (PCI) data security standard (DSS) and other compliance programs—and so can you.

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


Read this white paper to learn about a lean form of on-demand data integration technology called data virtualization. Deploying data virtualization results in business intelligence (BI) systems with simpler and more agile architectures that can confront the new challenges much more easily.

All the key concepts of data virtualization are described, including logical tables, importing data sources, data security, caching, and query optimization. Examples are given of application areas of data virtualization for BI, such as virtual data marts, big data analytics, extended data warehouse, and offloading cold data.

bizdomain online data  BI, business intelligence, operational intelligence, Hadoop, NoSQL, self-service BI, data virtualization, big data, on-demand data integration, lean data integration, JBoss Data Virtualization Read More