article thumbnail

DataOps For Business Analytics Teams

DataKitchen

Business analysts must rapidly deliver value and simultaneously manage fragile and error-prone analytics production pipelines. Data tables from IT and other data sources require a large amount of repetitive, manual work to be used in analytics. In business analytics, fire-fighting and stress are common.

article thumbnail

Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is a business intelligence analyst? A key role for data-driven decisions

CIO Business Intelligence

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization. More on BI: What is business intelligence? Real-time problem-solving exercises using Excel or other BI tools.

article thumbnail

Understanding Structured and Unstructured Data

Sisense

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

article thumbnail

9 Distinct Threats to Your BI Implementation

Jet Global

Risk to the business. The mechanical solution is to build a data warehouse. This is because people won’t use BI applications that are founded on irrelevant, incomplete, or questionable data. That’s because nothing will highlight data quality issues like seeing them pop up in a dashboard.

article thumbnail

Enable Multi-AZ deployments for your Amazon Redshift data warehouse

AWS Big Data

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.