In the past blogs, we have learned how to install Talend Open Studio, how to build a basic job loading data into Snowflake, and how to use a tMap component to build more complex jobs. In this blog, we will enable you with some helpful debugging techniques and provide additional resources that you can leverage as you continue to learn more about Talend Open Studio.
The information revolution - which holds the promise of a supercharged economy through the use of advanced analytics, data management technologies, the cloud, and knowledge - is affecting every industry. Digital transformation requires major IT modernization and the ability to shorten time data to insights to make the right business decisions. For companies, it means being able to efficiently process and analyze data from a variety of sources at scale.
In the last few years, we’ve seen the concept of the “Cloud Data Lake” has gained more traction in the enterprise. When done right, a data lake can provide the agility for Digital Transformation around customer experience by enabling access to historical and real-time data for analytics.
Bugfender is pleased to announce that José Jeria Mena, developer of the game-changing fitness app Social Steps, has won our latest competition and is now the proud owner of an iPhone XS.
I’ve read and heard a lot about how organizations need ‘data interpreters’ lately. For me, this raises the question of what do analytics departments do today?
The Yellowfin team spent their Wednesday at the She Loves Data event in Melbourne. It was brilliant. If you’re not familiar, She Loves Data (previously called Data Girls) is a data analytics initiative, that focuses on teaching and encouraging women to learn about data, technology, and analytics. They hold regular workshops for women in 6 different APAC cities to build a community for them to come together to learn, connect with each other, and have fun.
Data is the lifeblood of AI. An AI system needs to learn from data, as well as from humans, in order to be able to fulfill its function. Unfortunately, organizations are already struggling to integrate data from multiple sources to create a single source of truth on their customers, products, or other data. AI will not solve these data issues, it will only make them more pronounced.
