Fivetran and Atlan team up to power modern data governance
Joint customers can move faster with more visibility across their entire data stack, helping data teams collaborate better with increased trust in their data.
How Iceberg Tables Work In Snowflake | Demo
Iceberg Tables, a new type of Snowflake table available in preview, pairs Snowflake’s powerful performance engine and platform capabilities with open formats in external storage. In this video, you will get:❄ An overview of Apache Iceberg❄ A demo showing how Iceberg Tables support interoperability between different tools❄ A technical deep dive on how Iceberg Tables work in Snowflake Links to Iceberg resources.
Data Warehousing and Data Mesh: Different Types of Goals
The world is full of different types of goals. Consider football. The goal in football is at the end of the field. A runner either crosses the goal or they don't, when trying to make a touchdown. Or, consider basketball. In basketball, when a player shoots the ball, the player’s shot either goes through the net or it doesn’t. Alternatively, consider ice hockey. When a hockey player shoots the puck, it either goes into the net — or it doesn’t.
Future of Data Meetup | Apache Iceberg: Looking Below the Waterline
Apache Iceberg has become the most popular, fastest-growing, and widely adopted open table format in the big data space. Hear from (and ask your questions to!) some of the key partners leading the Iceberg roadmap and enhancements. AGENDA: Apache Iceberg for BI use cases.
New Research Finds Data Quality Chasm Looms as Organizations Strive for Data Fluency
Report from insightsoftware and Hanover Research reveals the gaps that need to be bridged to reach data fluency, noting challenges in data quality and connection.
BigQuery: Manage your workloads
Would you like to know how to manage your workloads efficiently? Are you interested in learning how to share the slots across different workloads/projects?
How to build a data pipeline
You'll need to understand the six key components of a data pipeline and overcome five important technical challenges.
What is DataOps? Leveraging Telemetry Data for Product-Led Growth
Any data-driven organization will tell you that the holy grail is faster time to insights. But the unfortunate truth is that business users often have to wait days — even weeks or months — to analyze the data they need. Behind the scenes, data engineering teams put a lot of work into joining disparate datasets, creating pipelines, and delivering a final data product back to their stakeholders for analysis.
SaaS in 60 - Natural Language Insights on Dashboards
You can now deliver AI-generated, natural language insights directly on sheets in Qlik Sense. With our new natural language object, you can include narrative interpretations and readouts for any context, such as an overall sheet, a group of visualizations, or an individual visualization. This capability allows all Qlik Sense users to benefit from NLG when exploring in dashboards, boosting data literacy and driving improved data storytelling.
What's Ahead in Data Management in 2023?
Data management is fundamental to every application. Managing this precious asset is an essential competency in modern businesses of every sort. Innovations in data platforms are being adopted, and data management approaches are evolving rapidly to keep pace. Increasingly, enterprises are converging their data warehouse, data lake, and other data management platforms onto distributed cloud-native infrastructures. As more types of data are consolidated into their platforms, enterprises implement more scalable DataOps pipelines and more comprehensive governance practices to manage it all.