Systems | Development | Analytics | API | Testing

February 2019

Delivering on Data Science with Talend: Getting Quality Data

Today, we are in the information age with a tremendous amount of data being created (as much as 90% of data being created in the last two years alone). This data comes from a wide range of sources and takes many different forms: human-generated documents and social media communications; transactional data that we use to run our businesses; and there is an ever-increasing proliferation of sensors producing streams of data.

6 Dos and Dont's of Data Governance - Part 1

One big mistake I see organizations make when starting out on their data governance journey is forgetting the rationale behind data. So don’t just govern to govern. Whether you need to minimize risks or maximize your benefits, link your data governance projects to clear and measurable outcomes. As data governance is a non-departmental initiative, but rather a company-wide initiative, you will need to prove its value from the start to convince leaders to prioritize and allocate some resources.

Cloud Data Warehouse Trends You Should Know in 2019

In October 2018, TDWI and Talend asked over 200 architects, IT and Analytics managers, directors and VPs, and a mix of data professionals about their cloud data warehouse strategy in a survey conducted in October 2018. We wanted to get real answers about how companies are moving to the cloud, especially with the recent rise of Cloud Data Warehouse technologies. For instance, we wanted to know if a cloud data warehouse (CDW) is seen as a key driver of digital transformation.

Automated Machine Learning: is it the Holy Grail?

Machine learning is in the ascendancy. Particularly when it comes to pattern recognition, machine learning is the method of choice. Tangible examples of its applications include fraud detection, image recognition, predictive maintenance, and train delay prediction systems. In day-to-day machine learning (ML) and the quest to deploy the knowledge gained, we typically encounter these three main problems (but not the only ones).

Data Warehouse Modernization and the Journey to the Cloud

To say that organizations today are facing a complex data landscape is really an understatement. Data exists in on-premises systems and in the cloud; data is used across applications and accessed across departments. Information is being exchanged in ever-growing volumes with customers and business partners. Websites and social media platforms are constantly adding data to the mix.

Spinning up Cloud-scale Analytics is now Even More Compelling with Talend and Microsoft

Today, we're excited to share two announcements that make adopting Microsoft Azure SQL Data Warehouse (ADW) a no-brainer. First, ADW significantly increased the lead over the competition with the new price-performance benchmarks published by GigaOm, showing exponential price-performance improvements over similar solutions.