Talend Reference Library

When choosing a data integration solution that best meets their needs, companies are confronted with many product choices, and multiple sources of information - including software vendors who will assure that their product is the one they need! In reality, the proposed solutions may or may not be appropriate.

To help you evaluate various solutions and technologies available on the market, and to compare open source data integration technology with other alternatives, this White Paper presents the top 10 reasons why organizations are choosing open source for their data integration needs. To support these top reasons, the White Paper includes proof points (31 in total) provided by actual users of open source data integration.

Today, many organizations are deploying new systems - RDBMS, business applications such as CRM or ERP, data warehouses, etc. Any new technology deployment in an enterprise information system requires the newly-deployed system to interoperate, in one form or another, with a number of other applications or databases. This interoperability, which is essentially based on the exchange of data between systems ("data integration"), guarantees the consistency of data in the overall information system.

This White Paper describes a number of real-life applications and databases interoperability scenarios and explains how an Open Source approach helps solving the interoperability challenge.

Founded in 1989, Bloor Research is one of the world's leading IT research, analysis and consultancy organizations.

In this Analyst White Paper, Research Director Philip Howard explains why web-based data, that includes not only clickstream data but also Web 2.0 user behavior information, is essential to analytic applications. He explains the complexity of incorporating this type of data in conventional analytic environments, and the technologies that are involved to optimize the process.

The white paper also describes a number of real-life use cases and their constraints and analyzes which technologies provide required capabilities.

Open source database solutions that provide enterprise-level functionality, services and support are revolutionizing today's marketplace.  If, like many other organizations, you are deploying - or considering deploying - the Ingres RDBMS to host your business applications such as CRM or ERP, data warehouses, etc., you will confronted with the requirement that these newly deployed systems interoperate, in one form or another, with a number of other applications or databases.

This interoperability, which is essentially based on the exchange of data between systems ("data integration"), guarantees the consistency of data in the overall information system. Talend, the industry's first pure open source play data integration vendor, and Ingres, the leading Business Open Source software company, have teamed up to bring you this complimentary White Paper which describes a number of real-life interoperability scenarios for Ingres and explains how an Open Source approach helps solving the interoperability challenge.

Over the past few years, open source has established itself as a key component of the overall data integration market. Many organizations have adopted this model for their data integration projects. These organizations span all industries, all continents, and all company sizes. More importantly, their projects range from ETL for data warehousing or business intelligence to operational data integration, data migration, data synchronization, etc.

This second volume of Practical Open Source Data Integration: Case Studies & Implementation Examples presents selected case studies, illustrating real-life implementations of open source data integration and its associated benefits.

When choosing a data integration solution that best meets their needs, companies are confronted with many product choices, and multiple sources of information - including software vendors who will assure that their product is the one they need! In reality, the proposed solutions may or may not be appropriate.

To help you evaluate various solutions and technologies available on the market, and to compare open source data integration technology with other alternatives, this White Paper presents the top 10 reasons why organizations are choosing open source for their data integration needs. To support these top reasons, the White Paper includes proof points (31 in total) provided by actual users of open source data integration.

Data integration (DI) is often seen as merely a technical discipline, but this ignores the vital role it plays in helping enterprises achieve their business goals. It is essential that business managers, as well as technical staff, understand how better DI can help deliver against key commercial goals, such as helping the organization become more efficient, agile, innovative and customer centric.

Telesperience research indicates a pattern of high and increasing demand for DI from the business, as well as a recognition that DI is a key strategy for lowering costs and improving business performance. However, most enterprises also report that their DI projects over-run on either cost or time (or both) and that DI costs are either too high or more than anticipated.

This paper explains why DI is an important weapon in an enterprise's competitive arsenal by analysing how poor DI inflates costs, by revealing the current DI drivers, and by explaining how DI can contribute to commercial success.

Telesperience's Research Director Teresa Cottam says: "Our research demonstrates that companies that are able to deliver DI projects quickly, reliably and at low cost will out-perform their rivals, because they will be able to exploit new technologies and insights to gain competitive advantage and reduce their costs."

Today, many organizations are deploying MySQL or MySQL Enterprise for extremely varied uses - from e-Business to Customer Relationship Management, from Data Warehousing to Accounting, from Technical Databases to Enterprise Resource Planning. Any new technology deployment in an enterprise information system requires the newly-deployed system to interoperate, in one form or another, with a number of other applications or databases. This interoperability, which is essentially based on the exchange of data between systems ("data integration"), guarantees the consistency of data in the overall information system.

This White Paper describes a number of real-life interoperability scenarios for MySQL Enterprise and explains how an Open Source approach helps solving the interoperability challenge.

Enterprise data integration needs are growing exponentially over time, as is the interest in open source technologies and the adoption of open source solutions. And, as information systems are becoming more heterogeneous, the global economy is imposing cost controls on IT Managers, both in terms of staff and software. With this in mind Talend conducted a survey to define the usage landscape of open source data integration and to profile users of this technology.

Consolidating the open source experience of over 1000 respondents, this White Paper discusses the most commonly used data integration technologies, their benefits, and the associated decision criteria. It also highlights the types of projects open source data integration is used for, and how it complements other data integration technologies.

Historically, public administrations have been the leading supporters of open source technology, especially - but not only - in Europe. The economic nature of these products has been one of the main factors of adoption, but as they have matured, these products offered other benefits that positioned them as viable alternatives to proprietary technology.

This White Paper presents the logic and reasons behind the adoption of open source by the public sector. It analyzes its benefits and presents concrete examples from public institutions in different countries.

Data governance is an outstanding business strategy that leads your company toward greater efficiency, lower risk and increased revenue. Proper management of data underpins the success many strategic initiatives. However, it is not always easy for others to see its value.

This white paper discusses the techniques that have been successful for data champions as they "sell" the importance of data governance to their company. It examines guidelines for optimal project selection, tracking the value of data governance and techniques for overcoming objections to a data governance program.

Most data integration processes have seen limited automation over the past decade despite many technology advances.

This White Paper by Industry Analyst Mark Madsen will help understand what data integration is, and especially the difference between Operational Data Integration and Analytic Data Integration. It highlights the benefits of open source for data integration, and provides a series of recommendations to make the integration job easier, repeatable and more productive.

Mark Madsen is president of Third Nature, a consulting and technology research firm focused on information management. Mark is an award-winning architect and former CTO whose work has been featured in numerous industry publications. He is an international speaker, a contributing editor at Intelligent Enterprise, and manages the open source channel at the Business Intelligence Network.

Founded in 1989, Bloor Research is one of the world's leading IT research, analysis and consultancy organizations.

In this InDetail product review, Research Director Philip Howard takes a close look at the features of Talend Open Studio, its advantages and drawbacks. This 11-page analyst study will help IT staff and decision makers get an independent angle on the leading open source data integration solution.

"In our view, Talend is the most enterprise oriented of the open source data integration vendors." -- Philip Howard, Bloor Research

With cost often viewed as one of the major reasons to adopt open source technologies, the return on investment (ROI) of open source must be determined precisely when looking at deploying data integration solutions. This ROI Study looks in detail at all project costs: license (development, runtime, maintenance...), training and rampup, development and maintenance time, hardware and operating system, IT operations, etc. It also considers many intangible elements such as reliability, predictability, time to market.

More than a theoretical report, the ROI Study provides not only hard numbers but also the tools IT organizations need to assess the return of investment of open source, and to compare this ROI with the one of alternative options: manual coding, and proprietary data integration solutions.

The amount and diversity of work done by data integration specialists has exploded since the turn of the twenty-first century. A lot of the growth comes from the emerging practice of operational data integration, defined as "the exchange of data among operational applications, whether in one enterprise or across multiple ones." Operational data integration involves a long list of project types, but it usually manifests itself as projects for the migration, consolidation, collocation, and upgrade of operational databases.

The purpose of this report is to identify the best practices and common pitfalls involved in starting and sustaining a program for operational data integration. The report defines operational data integration in terms of its relationship to other data integration practices, as well as by its most common project types. Along the way, it also looks at staffing and other organizational issues, followed by a list of technical requirements and vendor products that apply to operational data integration projects. The report also provides practical recommendations for the success of operational data integration projects.

TDWI Best Practices Reports are designed to educate technical and business professionals about new technologies, concepts, or approaches that address a significant problem or issue. Research for the reports is conducted via interviews and surveys of leading-edge user companies.

Over the past few years, open source has established itself as a key component of the overall data integration market. Many organizations have adopted this model for their data integration projects. These organizations span all industries, all continents, and all company sizes. More importantly, their projects range from ETL for data warehousing or business intelligence to operational data integration, data migration, data synchronization, etc.

This document presents a few selected case studies, illustrating real-life implementations of open source data integration and its associated benefits.

Founded in 1989, Bloor Research is one of the world's leading IT research, analysis and consultancy organizations.

In this Market Update, Research Director Philip Howard explains how the enterprise market for data integration is now less focused on traditional ETL and more centered on data integration as a broader concept. He looks at the requirements for enterprise-ready data integration platforms and examines the vendor landscape, including traditional players and disruptive technologies such as open source.

"In any market, open source represents a potentially disruptive approach. However, relatively few vendors are effectively organised to take advantage of such disruption. Talend is an exception." -- Philip Howard, Bloor Research

The 451 group is an independent technology-industry analyst company focused on the business of enterprise IT innovation. The company's analysts provide critical and timely insight into the market and competitive dynamics of innovation in emerging technology segments.

This report titled Climate Change: User Perspectives on the Impact of Economic Conditions on Open Source Software Adoption, is based on a survey of more than 1,700 open source software users and customers, assessing their current attitudes on the key benefits of open source software, including cost and flexibility.

The report serves as a practical guide for understanding the financial benefits of open source. It also includes an updated version of The 451 Group's guide for calculating the financial benefits of open source in enterprise IT projects. It provides a basic financial analysis approach and calculator to identify and capture the costs and potential benefits of open source software.

Note: This report is made available to you through your relationship with Talend. It was researched and published by The 451 Group, an independent industry analyst company, and is part of The 451 Group's Commercial Adoption of Open Source service. The report is available to the named recipient only and must not be shared externally to your organization

Data integration plays a vital role in the commercial agility and operational efficiency of enterprises. In this data sheet, UK-based analysts Telesperience summarise the findings from a primary research project into data integration in high transaction industries. Among other topics, this paper looks at what is driving data integration today, outlines the cost implications of poor data integration, examines how confident enterprises are that they can deliver data integration projects on time and to budget, and reveals what data integration goals are for 2010-11.

IDC is the premier global provider of market intelligence, advisory services, and events for the information technology, telecommunications, and consumer technology markets.

In this IDC White Paper sponsored by Talend, analyst Carl Olofson discusses the data integration market, examines the approach taken by Talend, and shows how the combination of Talend's technical approach and its open source licensing overcomes key barriers to adoption of data integration.

It has been generally accepted that the open source model works well for delivering software support and other services on top of well-understood software technology in commodity markets such as operating systems and general-purpose relational DBMS.

Talend is demonstrating, however, that this model may also be applied as a go-to-market strategy to build a business based on new technology, such as that of the still rapidly evolving data integration market. Talend's product line, which is positioned to offer scalable, incremental enterprise data integration with components that are easy for non-technical staff to use, breaks the mold for open source, and its success could shake up the software business.

The 451 group is an independent technology-industry analyst company focused on the business of enterprise IT innovation. The company´s analysts provide critical and timely insight into the market and competitive dynamics of innovation in emerging technology segments.

In this report titled Cost Conscious: a practical guide for understanding and calculating the financial benefits of open source for enterprise IT projects, 451 analysts take a hard look at how to calculate the return on investment of open source.

Like any technology decision, the adoption of open source requires a business justification.  This Report from The 451 Group serves as a practical guide for understanding and calculating the financial benefits of open source. It includes a calculator tool for use in quantifying the financial benefits.

Note: This report is made available to you through your relationship with Talend. It was researched and published by The 451 Group, an independent industry analyst company, and is part of The 451 Group´s Commercial Adoption of Open Source service. The report is available to the named recipient only and must not be shared externally to your organization

Processing very large data sets provides unique constraints, especially when time windows available for this processing are shrinking.

This Technical White Paper presents a variety of technologies that are available for accelerating the processing of large data volumes, including massive parallelization, optimized data-set-mode processing based on Map Reduce, grid deployment, and load balancing.

As information systems grow in complexity and volume, the need for scalability and versatility of data integration increases. In this White Paper, Bill Inmon explains how data integration grows from simple data movement to complex transformation functions, and how modern, pervasive and scalable data integration technology enables organizations of all sizes to deploy data integration technology, without the usual restrictions imposed by the deployment costs of traditional integration products.

Bill Inmon, world-renowned expert, speaker and author on data warehousing, is widely recognized as the "Father of Data Warehousing". He was also voted as "One of the Ten IT People Who Mattered in the Past Forty Years" by the ComputerWorld Magazine's July 2007 issue.

All companies deploying SAP need to align all other applications and systems - whether internal or external - as a means of collaborating with partners and vendors, streamlining their operations, and maximizing their IT investments.

SAP is highly successful and popular, but it is also a large, unique, and complex system environment and presents many challenges to companies who want to integrate it with third-party systems.

This Technical White Paper explains how to fill a broad range of integration needs without expensive IT development costs.

In the beginning, open source solutions were the shiny play things of the techno crowd. After all, they were fun, new, and most importantly, free. No one would have considered using them in any real world corporate IT shops...

Today, open source solutions are not only being considered, they are being implemented by large and small enterprises -- at rates that are mind-boggling. This paper examines the challenges faced by organizations today regarding their BI, data integration, and data warehousing environments, why traditional solutions fall short, and the rise of upstart open source companies.

A thought leader, visionary, and practitioner in the rapidly growing fields of business intelligence and customer focused-strategy - Claudia Imhoff, Ph.D. is a popular and dynamic speaker and internationally recognized expert on analytical CRM, business intelligence, and the infrastructure to support these initiatives.

Founded in 1989, Bloor Research is one of the world's leading IT research, analysis and consultancy organisations.

Data migration projects frequently overrun their budgets, get delayed or, in extreme circumstances, get cancelled. A major reason behind these failures is because the techniques and disciplines of data migration are not treated seriously enough or are not well enough understood. This white paper highlights the major issues and complexities involved in data migration; it includes practical recommendations by the leading independent analyst firm for the success of migration projects.

"In our view, data migration has historically been under-valued, under-resourced and not treated with the attention it deserves." -- Philip Howard, Bloor Research

Founded in 1989, Bloor Research is one of the world's leading IT research, analysis and consultancy organizations.

In this Spotlight Report, Research Director Philip Howard explains why data discovery is of fundamental importance to data integration, data quality, and many other projects ranging from business intelligence through master data management to data governance and data archival. Nevertheless, data discovery has not traditionally been treated as a market or requirement in its own right. As a result, it is time to consider the importance of data discovery, and its requirements.

"We believe that the ability to discover and understand the relationships that exist across your data, wherever it resides, is of fundamental importance to a number of IT disciplines." -- Philip Howard, Bloor Research

Matching technology plays an important role in achieving a single view of customers, parts, transactions or almost any type of data. Often used to identify duplicates and near-duplicates, matching technology is vital to providing data that is fit-for-use in enterprise applications.

This white paper outlines the basic theories and strategies of record matching. It describes the nuances of deterministic and probabilistic matching and the algorithms used to identify relationships within records. It covers the processes you can use in conjunction with matching technology to transform raw data into powerful information that drives success in enterprise applications like CRM, data warehouse and ERP.

Over the past few years, commercial open source vendors have been providing a real alternative to proprietary players. In the data integration space, enterprise grade open source solutions are adopted by many organizations for their data integration and data quality projects. These organizations span all industries, all continents, and all company sizes. More importantly, their projects range from ETL for business intelligence to operational data, data quality, master data management, etc.

This third volume of Practical Open Source Data Integration: Case Studies & Implementation Examples presents selected case studies, illustrating real-life implementations of open source data integration and its associated benefits.

Poor-quality data affects all data-related projects and refers to the state of completeness, validity, consistency, timeliness and accuracy that makes data appropriate for a specific use.

This Technical White Paper presents the main challenges of data quality and drills into specific uses of data profiling and data cleansing. It highlights, through 32 distinct use cases, how open source data quality technology can be used to alleviate issues related to poor-quality data.

In most organizations today, data and other information are managed in isolated silos by independent teams using various data management tools such as data quality, data integration, master data management, etc. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools.

The purpose of this report is to help organizations plan and execute effective UDM efforts. Many need the help, because UDM is a relatively new shift in best practices for data management. Toward that end, the report drills into the business initiatives that need UDM, the data management practices and tools that support it, and the organizational structures that enable the cross-functional collaboration that’s critical to UDM success. The report also provides practical recommendations for the success of unified data management projects.

TDWI Best Practices Reports are designed to educate technical and business professionals about new technologies, concepts, or approaches that address a significant problem or issue. Research for the reports is conducted via interviews and surveys of leading-edge user companies.

Master Data Management (MDM) has received growing attention recently as an essential component of information management alongside data governance and data quality. More and more, organizations are turning to Master Data Management as a key enabler in improving the timeliness, quality and reliability of business intelligence with the ultimate goal of improving business performance. Increasing regulatory requirements and the recent financial crisis have ensured that Master Data Management is increasingly finding its way onto the business agenda.

Information Difference conducted a survey of both end-user organizations and systems integrators aimed at gaining deeper insight into MDM implementations and their success factors. This report summarizes and analyzes the results of that survey, and presents practical recommendations on the "do and don't" of MDM. It also contains some enlightening findings on the use of open source and manual coding in MDM projects.

The Information Difference is an analyst firm focusing on Master Data Management (MDM). Its founders are pioneers who helped shape the MDM industry, with in-depth MDM global project experience.

Many organizations consider high quality master data as a key strategy for accomplishing corporate objectives. Proper master data management (MDM) is indeed extremely valuable when available to enterprise business processes and analytics, however, master data projects are often politically challenging, architecturally complex, time intensive and expensive.

MDM is a natural extension to data integration and data quality. Open source MDM introduces a new, more accessible approach. It reduces implementation complexity, time to value and cost. In fact, as in many other markets, open source helps organizations overcomes obstacles and realize their goals.

This White Paper provides an explanation of why the time is right for open source MDM, and predicts the effects of open source on the MDM marketplace.

Projects addressing data quality or master data management frequently struggle to get approved by senior management, and only around 60% of such projects proceed with a proper business case - causing high rates of cancellation and failure.

This white paper explains the key elements for building a proper, quantified business case. It presents the measures that are favored by corporate finance departments, and helps develop a strong business case for data quality and MDM projects. A number of real-life examples with quantifiable benefits are also included.

Armed with the materials in this white paper, you will be in a good position to deliver a high quality business case for your data quality or MDM project!

The Information Difference is an analyst firm focusing on Master Data Management (MDM). Its founders are pioneers who helped shape the MDM industry, with in-depth MDM global project experience.

Reference data is the lifeblood of an organization but inconsistencies across business units or systems can lead to inefficient processes and inaccurate analytics. Most organizations understand the importance of consistent reference data but struggle to ensure consistency and to police compliance to a central reference data standard. Master reference data makes operational data more accurate, simplifies synchronization and migration projects and improves effectiveness of MDM.

Creating master reference data can be very simple. Typically, an organization will start small and then grow the master as acceptance spreads throughout the organizations. This white paper presents some key considerations for creating a reference data master.