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Software Functionality Revealed in Detail
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 integration maturity model 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

ERP for the Oil and Gas Industry (Upstream)

The model of ERP systems for the upstream oil and gas sector addresses the particularly specialized business model of this industry. It is common practice for companies, individuals, and government agencies to form partnerships to explore, develop, and share production of oil wells. More often than not, this is a short-term alliance rather than a long-term partnership, and business structuring must therefore be flexible at initial set-up and throughout the lifespan of the venture. This model of ERP systems includes criteria for financials, human resources, production data capture and reporting, maintenance management, and supply chain management (SCM) functionality. 

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Documents related to » integration maturity model data

There Is No Execution without Integration


In fast-paced, low-margin manufacturing environments, companies must embrace technology in order to solidify or gain competitive advantages. It is equally important to avoid adopting technology for technology’s sake. Find out how leading companies are focusing on efficiency and cost reduction by integrating manufacturing execution systems (MES) or manufacturing intelligence (MI) with enterprise resource planning (ERP).

integration maturity model data  Execution Integration , MES Integration Systems , ERP Manufacturing Execution , MI Manufacturing Execution . Executive Summary Many manufacturers today are getting caught on the wrong side of a technology adoption wave that is quickly gaining momentum. Of the more than 200 surveyed manufacturers 54% are planning on adopting MI (Manufacturing Intelligence) within the next 24 months. Additionally, 56% of manufacturers having already implemented MES (Manufacturing Execution Systems) did so within the past 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.

integration maturity model data  Requirement , Schedule , Integration , Project , Analysis , Audit , Best Practices , Checklist , Conversion , Cost , Download , Guide , Issues , Specialist , Essential Data Migration , Scope Data Migration Effort . Data migration is the one-time movement of data from a legacy source, or multiple sources, to a new target database. This simple concept and requirement can drive a scope that is much larger than expected. A data migration requirement can be driven by a range of initiatives, such as an Read More

A One-stop Event for Business Intelligence and Data Warehousing Information


The Data Warehousing Institute (TDWI) hosts quarterly World Conferences to help organizations involved in data warehousing, business intelligence, and performance management. These conferences supply a wealth of information aimed at improving organizational decision-making, optimizing performance, and achieving business objectives.

integration maturity model data  design of the platform. Integration questions center on whether the current systems will integrate with the new software—and more importantly, how they will integrate. Data Integration The theme of data integration included all the topics related to implementing a data warehouse solution. Included were data profiling; data transformation; data cleansing; source and target mapping; data cleansing and transformation; and extract, transform, and load (ETL) development. It is important not to underestimate Read More

Developing a Universal Approach to Cleansing Customer and Product Data


Data quality has always been an important issue for companies, and today it’s even more so. But are you up-to-date on current industry problems concerning data quality? Do you know how to address quality problems with customer, product, and other types of corporate data? Discover how data cleansing tools help improve data constancy and accuracy, and find out why you need an enterprise-wide approach to data management.

integration maturity model data  Management: Data Profiling, Data Integration and Data Quality ) by David Loshin that discusses this topic in detail and is recommended reading. Types of Data Involved in Ma naging Data Quality A data quality program involves many different types of data. The data may be current or historic, detailed or summarized, and may have a structured, unstructured, or semi-structured format. It may consist of master business entity or master reference data, or activity data created by business transaction (order Read More

Is the SaaS Model Right for You?


For IT departments drowning in complex and expensive software maintenance chores, the software-as-a-service (SaaS) model can ease the burden. SaaS reduces complexity by outsourcing most of the infrastructure needed to run software applications, and reduces costs by charging only for what is consumed. But you can also adopt a hybrid SaaS model, in which some systems are outsourced and others are kept in-house. Learn more.

integration maturity model data  this application/project dependent on integration with other applications or data? Will we have to customize the application to work in a cloud environment? Vendor Support: Does the cloud provider provide migration support, and support for service/performance issues? Vendor Compliance: Does the cloud provider meet all necessary regulatory requirements for this project/ application/data? Are there comparable instances supported by the provider meeting the same requirements? Is the provider open to audit 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.

integration maturity model data   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.

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Data Enrichment and Classification to Drive Data Reliability in Strategic Sourcing and Spend Analytics


Spend analytics and performance management software can deliver valuable insights into savings opportunities and risk management. But to make confident decisions and take the right actions, you need more than just software—you also need the right data. This white paper discusses a solution to help ensure that your applications process reliable data so that your spend analyses and supplier risk assessments are accurate, trustworthy, and complete.

integration maturity model data  spend analytics,performance management software,spend analyses,supplier risk assessments,data enrichment and classification Read More

Network Data Protection Playbook: Network Security Best Practice for Protecting Your Organization


Malicious hacking and illegal access are just a few of the reasons companies lose precious corporate data every year. As the number of network security breaches increase, companies must find ways to protect data beyond the perimeter of their businesses. But how do they build a data-defensible architecture that will protect data on an ever-evolving network? The answer: by first developing an in-depth defense strategy.

integration maturity model data  Information Architecture | Data Integration | Data Integration Architecture | Data Integrator Architecture | Data Legislation | Data Loss | Data Loss Prevention | Data Management | Data Memory Solutions | Data Migration | Data Model | Data Modeling | Data Modeling Architecture | Data Network Architecture | Data Policy | Data Privacy | Data Privacy ACT | Data Privacy Breaches | Data Processed | Data Protection | Data Protection ACT | Data Protection Analysis | Data Protection and Recovery | 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.

integration maturity model data  Data Management , Data Integration , Data Sets , Data Integrity , Data Cleansing Projects , After presenting a case study “Supply Chain Data- Dont let it be your weakest link!''” with Alcon Laboratories at the TCU Global Supply Chain conference in April 2005 there were a flurry of questions from the attendees. While the presentation was mainly focused on the value of quality data in the supply chain and in todays automated mass sharing of information with internal and external customers, we had 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.

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Data Storage in the Cloud-Can you Afford Not To?


Storing data in the cloud using Riverbed Technology’s Whitewater cloud storage gateway overcomes a serious challenge for IT departments: how to manage the vast, and ever-growing, amount of data that must be protected. This paper makes the business case for cloud storage, outlining where capital and operational costs can be eliminated or avoided by using the cloud for backup and archive storage.

integration maturity model data  data storage in the cloud,cloud data storage,online data storage,offsite data storage,data storage cloud,data storage solution,data storage business,data storage,data storage internet,data storage service,best cloud storage,online data storage backup,microsoft cloud storage,cloud services,cloud storage providers 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.

integration maturity model data  big data,data management,analytics,SAP Read More