Talend Fall ’18 is here! We’ve released a big update to the Talend platform this time around including support for APIs, as well as new big data and serverless capabilities. You will see blogs from my colleagues to highlight those major new product and features introductions. On my side, I’ve been working passionately to introduce Talend Data Catalog, which I believe has the potential to change the way data is consumed and managed within our enterprise.

AstraZeneca plc is a global, science-led biopharmaceutical company that is the world’s seventh-largest pharmaceutical business, with operations in more than 100 countries. The company focuses on the discovery, development, and commercialization of prescription medicines, which are used by millions of patients worldwide.

Times are tough – adversity is hitting our public sector and healthcare agencies from every angle. Budgets and resources are stretched beyond breaking point with many agencies facing multi-million real-term cuts. Combine this with an increase in complex demand, heightened public scrutiny and a continued expectation of improvement; something must change.

This month we released several new features in beta, including query scheduling, new BigQuery ML models and functions, and geospatial types and queries. We also released the ORC ingest format into GA. Let’s take a closer look at these features and what they might mean for you.

How do you protect the stability of the work you’ve already done, while evangelizing experimentation, exploration and progress within your organization? The rapid evolution in business intelligence and analytics capabilities is both exhilarating and overwhelming.

BigQuery, Google Cloud’s serverless, highly scalable, low-cost, enterprise data warehouse, was designed to make data analysts productive. With no infrastructure to manage, customers can focus on analyzing data using familiar Standard SQL, while simplifying database administration and data operations. Large enterprises, mid-market growing organizations, and cloud native startups across the globe can use BigQuery to perform analytics at scale with equal ease.

For part two of this blog I’m seated in a café in Sydney Harbour in the shadow of the Opera House and in full view of Sydney Harbour Bridge. Why’s that significant? Well it’s not really, other than this is the 2nd stop on our Data Revolution Tour where the keynote I delivered was essentially on this very topic. Let me explain.

We’ve all dreamed of going to bed one day and waking up the next with superpowers – stronger, faster and even perhaps with the ability to fly. Yesterday that is exactly what happened to Tom Reilly and the people at Cloudera and Hortonworks. On October 2nd they went to bed as two rivals vying for leadership in the big data space. In the morning they woke up as Cloudera 2.0, a $700M firm, with a clear leadership position. “From the edge to AI”…to infinity and beyond!

As an entrepreneur and a CEO of a startup, I think it’s vital to have a mentor. You often come to critical junctures and that’s when it can be invaluable to speak to someone. You can’t talk to your colleagues though because you need to motivate them and keep the organization growing. That’s why having an external mentor is very helpful.

BigQuery is a fast, highly scalable, cost-effective, and fully-managed enterprise data warehouse for analytics at any scale. As BigQuery has grown in popularity, one question that often arises is how to copy tables across locations in an efficient and scalable manner. BigQuery has some limitations for data management, one being that the destination dataset must reside in the same location as the source dataset that contains the table being copied.