Sisense

JANUARY 14, 2021

Users open their dashboards expecting every chart to be fully functional and accurate; if they encounter a broken chart, distrust of the dashboard or the underlying data is a natural reaction. The Billie BI team has decided to share the code for their testing project to help other data teams using Sisense for Cloud Data Teams. “We

Dashboards 85

Dashboards Testing Business Intelligence Interactive 85

datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

datapine

AUGUST 14, 2019

Exclusive Bonus Content: Download Our Free Data & Science Checklist! Geet our bite-sized free summary and start building your data skills! Therefore, there are numerous data science tools and techniques that provide scientists with an easier, more digestible workflow and powerful results. Our Top Data Science Tools.

Data Science 214

Data Science Statistics Business Intelligence Visualization 214

Domino Data Lab

JULY 22, 2019

But the business logic kept getting more and more progressively rolled back into the middle layer, also called application servers, web servers, later being called middleware. Then in the bottom tier, you had your data management, your back office, right? It’s also a driver for data science. Then things changed.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Smarten

SEPTEMBER 6, 2019

SSDP (otherwise known as self-serve data preparation) is the logical evolution of business intelligence analytical tools. With self-serve tools, data discovery and analytics tools are accessible to team members and business users across the enterprise. What is SSDP? Can SSDP Truly Make Analytics Self-Serve?

Analytics 51

Analytics IT Business Intelligence Testing 51

Peter James Thomas

AUGUST 12, 2018

Let’s cover what can go wrong (note: this section is not intended to be exhaustive, links are provided to more in-depth articles where appropriate): Accuracy of Data that is captured. A number of factors can play into the accuracy of data capture. Honesty of Data that is captured. How to Measure the Unmeasurable.

Metrics 49

Metrics Statistics Data Quality Measurement 49

Domino Data Lab

FEBRUARY 4, 2019

People who attended JupyterCon 2017–2018 can attest, an “industry poster session” includes an open bar, catered hors d’oeuvres, lots of mingling … to paraphrase feedback from JupyterCon, “As a tech person, would I get up extra early to meet strangers for coffee at 8:00 am? Lack of data, or data quality issues (silos).

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66