Systems | Development | Analytics | API | Testing

What are folders, projects, and datasets and how do they come together to support warehousing fundamentals like security and cost management? In this episode of BigQuery Spotlight, we’ll review the BigQuery resource model and how this resource hierarchy is reflected in the Cloud Console, where you’ll interact with and analyze your BigQuery data. Moreover, we’ll give you some helpful tips when it comes to structuring your own BigQuery resources. Watch to learn the best way to structure your BigQuery deployments!

In our fourth Kong and Okta tutorial, we will implement a basic access control policy based on Okta's groups and planes.

At the Modern Data Stack EMEA Conference, Fivetran Customer Success Manager Maeve Byrne is joined by Igor Chtivelband, Co-Founder and VP of Data & CRM at Billio.io and Bahadir Sahin, Director of Data & Analytics at Onfido. The panel shares their journeys toward better customer engagement, fueled by faster access to more data.

Watch how BT is leveraging Qlik to democratize data across its consumer division and deliver personalized experiences to customers.

Calculating the return on your marketing investment can be challenging and time-consuming. As there are various marketing sources and channels that create new sales opportunities, it’s important to know which ones are working best to help you meet your business goals.

Teri will show you how you can incorporate Salesforce (relational data) into a MongoDB collection (non-relational data) to give your customers a unified customer experience. The webinar will focus on the piece of the puzzle where we read Salesforce data and format it into the shape needed to go into a Mongo collection (a collection is the term MongoDB uses for a data set like a table in a relational database). We’re showcasing the ability to go back and forth from NoSQL to SQL for a unified customer experience.

We are happy to introduce Phil Voulgaris - SmartBear Product Marketing Lead for ReadyAPI. Watch the interview to learn more about Phil, why he likes the API technology and what we should expect in the future.

What kind of tools and infrastructure does a company need in order to build, train, validate and maintain data-based models as part of products? The straight answer is - “it depends.” The longer one is: “MLOps.” It is far too early to determine the “best” patterns and workflows for Data-Science, Machine- and Deep-Learning products. Yet, there are numerous examples of successful deployments from businesses both big and small.