article thumbnail

The data flywheel: A better way to think about your data strategy

CIO Business Intelligence

Every day, it helps countless organizations do everything from measure their ESG impact to create new streams of revenue, and consequently, companies without strong data cultures or concrete plans to build one are feeling the pressure. Some are our clients—and more of them are asking our help with their data strategy.

article thumbnail

Enable business users to analyze large datasets in your data lake with Amazon QuickSight

AWS Big Data

Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. As part of their solution, they are using Amazon QuickSight to unlock insights from their data.

Insiders

Sign Up for our Newsletter

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

Trending Sources

article thumbnail

What you don’t know about data management could kill your business

CIO Business Intelligence

In reality MDM ( master data management ) means Major Data Mess at most large firms, the end result of 20-plus years of throwing data into data warehouses and data lakes without a comprehensive data strategy. Contributing to the general lack of data about data is complexity.

article thumbnail

Achieving Trusted AI in Manufacturing

Cloudera

With the ability of manufacturers to store a huge volume of historical data, AI can be applied in general business areas of any industry, like developing recommendations for marketing, supply chain optimization, and new product development. Develop a data strategy built on a robust data platform.

article thumbnail

Straumann Group is transforming dentistry with data, AI

CIO Business Intelligence

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Business users will also perform data analytics within business intelligence (BI) platforms for insight into current market conditions or probable decision-making outcomes.

article thumbnail

Case study: Policy Enforcement Automation With Semantics

Ontotext

They are expected to understand the entire data landscape and generate business-moving insights while facing the voracious needs of different teams and the constraints of technology architecture and compliance. Evolution of data approaches The data strategies we’ve had so far have led to a lot of challenges and pain points.