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APIs for Dummies

Open your platform to new business opportunities while improving time to market and developer productivity with APIs. Watch this on-demand webinar to discover: How to create user-friendly APIs Best practices for API-first design How to field test your APIs To view this On Demand Webinar, please fill out the form.

Introduction to Talend Data Catalog

The newly introduced Talend Data Catalog, allows companies like yours to organize their data at scale, making it more accessible than ever before to address data challenges as a team, head-on. Talend Data Catalog automatically crawls, profiles, organizes, links, and enriches all your metadata, always keeping it up to date using smart profiling and automatic relationships. [style-full-width-content type="video" url="https://player.vimeo.com/video/306689786"] READ RESOURCE

Google BigQuery - Everything You Need to Know to Go Big with BQ

Research firm IDC made a remarkable prediction last year. According to its report, the amount of data produced globally will reach 163 zettabytes (1 ZB = 1 trillion GB) by 2025, a ten-fold increase from 2016. While the gargantuan increase in the amount of available data might seem like a great thing for business, many companies lack the tools needed to q READ RESOURCE

Cloud Data Warehouse Trends for 2019

How well does a cloud data warehouse prepare organizations for digital transformation? Increasingly, companies are adopting them for a wide variety of use cases, but do they actually help companies become more data-driven? TDWI and Talend conducted a survey of more than 200 companies in September-October 2018. Respondents noted that adopting CDWs were critical to increasing speed, performance, and lower costs, but when adopted alone, presented a number of challenges. A CDW was not eno

Create Data You Can Trust: How Your Data Integration Strategy Fuels Quality Data

There is more data available to the enterprise than ever before. An almost incomprehensible amount of data is created from a dizzying array of sources every day. And data-driven business intelligence is often the competitive differentiator between organizations. In order to extract value out of that data, companies need a data integration

Data Integration Success Stories

Data integration can be a challenge. Examples of data integration projects that haven’t achieved their required goals are abundant. But with the enterprise imperative to use data as a competitive differentiator, and to derive business intelligence from your own data, getting data integration right is now more important than ever.

Beyond ETL: Creating a Future-Proof Data Integration Strategy

It’s a given that companies must harness the data revolution to drive competitive advantage, but dealing with the enormous amount of enterprise data is a challenge. Two and a half quintillion bytes of data are created every day, and the volume of data is doubling each year. In addition, we are experiencing a time of accelerating change

Are You Ready for the Data Revolution?

The data revolution is here. 2.5 quintillion bytes of data are produced every single day, and more data is being produced today than at any time in human history. But how valuable is that data to your organization? The most successful companies in the world have one thing in common: they are intensely data-driven. In fact, data in

From Data Lake to Data Swamp - How the Legacy Trap Stifles Innovation

Companies depend on the rapid evolution of technology to meet their data integration needs. But many find themselves stuck in something called the “legacy trap.” The legacy trap is what happens when companies and organizations try to manage new technology with existing or outdated processes. The results are the inability to effectively implement new data tools and a tremendous waste of resources, especially when it comes to the use of a data lake. READ RESOURCE

Speed and Scale: Advanced Analytics with Machine Learning

Artificial Intelligence and Machine Learning (ML) can turn massive amounts of data into deep insights that drive revenue and decrease costs. But ML’s not an island – in fact, it’s carried out most successfully when paired with advanced analytics. To facilitate the best analytics work, enterprises need the right platforms and tools to load data, prepare it, ensure high-quality and integrate with corporate data governance processes. How can you get all that working harmoniously, e
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