Sisense

JANUARY 14, 2021

However, the methods they had at their disposal initially couldn’t keep up with their growing user base and the ever-evolving world of big data. 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.

Dashboards 85

Dashboards Testing Business Intelligence Interactive 85

Smart Data Collective

APRIL 13, 2021

In the modern world of business, data is one of the most important resources for any organization trying to thrive. Business data is highly valuable for cybercriminals. They even go after meta data. Big data can reveal trade secrets, financial information, as well as passwords or access keys to crucial enterprise resources.

Testing 122

Testing Behavioral Analytics Data-driven Big Data 122

datapine

NOVEMBER 27, 2019

Data exploded and became big. Spreadsheets finally took a backseat to actionable and insightful data visualizations and interactive business dashboards. The rise of self-service analytics democratized the data product chain. We all gained access to the cloud. How can we make it happen?

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

datapine

NOVEMBER 19, 2019

Currently, popular approaches include statistical methods, computational intelligence, and traditional symbolic AI. In business intelligence, we are evolving from static reports on what has already happened to proactive analytics with a live dashboard assisting businesses with more accurate reporting.

Technology 279

Technology Internet of Things IT IoT 279

O'Reilly on Data

MAY 21, 2019

For example, in a July 2018 survey that drew more than 11,000 respondents, we found strong engagement among companies: 51% stated they already had machine learning models in production. With all the hype around AI, it can be tempting to jump into use cases involving data types with which you aren’t familiar. Source: O'Reilly.

Machine Learning 234

Machine Learning Technology Deep Learning Data Science 234

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. Integrity of statistical estimates based on Data. million ± £0.5

Metrics 49

Metrics Statistics Data Quality Measurement 49