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BI

Panel recap: What Is DataOps observability?

Data teams and their business-side colleagues now expect—and need—more from their observability solutions than ever before. Modern data stacks create new challenges for performance, reliability, data quality, and, increasingly, cost. And the challenges faced by operations engineers are going to be different from those for data analysts, which are different from those people on the business side care about. That’s where DataOps observability comes in.

How To Build A High-quality BI Dashboard With The Best Software Test Manager

Business intelligence (BI) involves converting data into valuable insights using software and services. It influences a company’s strategic and tactical business preferences. BI tools access and analyze data sets and show analytical results in the form of reports, graphs & charts, dashboards, summaries, and maps. This process provides in-depth insight into the situation of the business.

Being a Steward of Data and Insights - Robert Brown

This episode features an interview with Robert Brown, the Senior Director of Research for the Venture Forward Initiative at GoDaddy. This is his 13th year at GoDaddy, having started as Director of Database Marketing. Prior to GoDaddy, Robert served as Director of Pulte Homes for 9 years. On this episode, Robert talks about tiering data for smarter decisioning, developing intrinsic motivation in employees, and being a successful steward of data and insights.

Discover the Advantages of Having Global Views from Angles for Oracle

The move to the cloud continues at a fast pace and if your organization embraces the future of operational reporting, then you need a plan to ensure consistent enterprise-wide reporting during your cloud journey. A top challenge of cloud migration is the need to produce consolidated reporting and analytics that cover all your Oracle ERP instances.

How Fivetran Ensures That Data Moves Reliably Through Data Pipelines

Fivetran, the provider of connectors that feed data into data pipelines, has had a long-standing, symbiotic relationship with Snowflake. In this episode of “Data Cloud Now,” Gautam Srinivasan, Snowflake India Correspondent chats with TJ Chandler, Managing Director for the APAC Region at Fivetran, about that relationship and about Fivetran’s mission “to make access to data as simple and reliable as electricity.”

Snowflake Announces Intent to Acquire Myst

Snowflake customers leverage the Data Cloud to bring all their data together and capitalize on the near-infinite resources of the cloud. But how can this data be used to look ahead? How can we use yesterday’s evidence to plan for tomorrow? The answer—time series forecasting. Time series forecasting is one of the most applied data science techniques in business. It is used extensively in supply chain management, inventory planning, and finance.

Top 3 Data and Analytics Trends to Prepare for in 2023

2022 was without a doubt a landmark year for business intelligence (BI) and analytics. With continued development of innovative and sophisticated technologies such as contextual analytics, analysis of our business data is more accessible than ever before. Many of these same trends will continue to grow into 2023, but the data analytics space is ever evolving.

Happy New Year from Yellowfin: Our 2023 Commitments

Happy New Year from the Yellowfin team, and welcome to our 2023 wrap-up! Following a year full of product feature updates, company changes and new initiatives, this blog provides a helpful summary for all our customers and followers on our future 2023 product roadmap for the Yellowfin embedded analytics suite, and a look back at last year’s biggest news.

How to Integrate BI and Data Visualization Tools with a Data Lake

For the past 30 years, the primary data source for business intelligence (BI) and data visualization tools has generally been either a data warehouse or a data mart. But as enterprises today struggle to cope with the growing complexity, scale, and speed of data, it’s becoming clear that the data tools of 30 years ago weren’t designed to handle the enterprise data management challenges of today - especially with the growing variety and amounts of data that enterprises are generating.