DataRobot

JANUARY 20, 2022

— Snowflake and DataRobot integration capability delivers automated production of clinical and population health datasets and AI risk detection models that accelerate the delivery of real-time predictive insight to clinicians and operational managers wherever it’s needed. Grasping the digital opportunity.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

Data Warehouse 94

Data Warehouse Optimization Dashboards Interactive 94

IBM Big Data Hub

OCTOBER 16, 2023

Foundation models can use language, vision and more to affect the real world. GPT-3, OpenAI’s language prediction model that can process and generate human-like text, is an example of a foundation model. They are used in everything from robotics to tools that reason and interact with humans.

Risk 72

Risk Modeling Management Metadata 72

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 74

Analytics Data Warehouse Data Lake Metadata 74

IBM Big Data Hub

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Watsonx comprises of three powerful components: the watsonx.ai

Data Science 78

Data Science Data Analytics Prescriptive Analytics Analytics 78

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

Birst BI

OCTOBER 30, 2018

Because the data describing each transaction was in a database, this made it easy to retrieve and summarize multiple transactions together. This data retrieval and summarization capability gave rise to what we now know as the business intelligence industry. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smarten

JUNE 5, 2019

CEO Patel, says, “As the Smarten product evolves, it is truly exciting to see the ways in which business users, data scientists, IT staff and business managers have embraced and adopted advanced analytics as part of the day-to-day and strategic business decision process.”

Analytics 40

Analytics Predictive Modeling Data Analytics Data Warehouse 40

CIO Business Intelligence

MAY 10, 2022

Data management consultancy, BitBang, says CDPs offer five key benefits : As a central hub for all your customer data, they help you build unified customer profiles. They eliminate data silos, and, unlike a traditional data warehouse, CDPs don’t require technical expertise to set up or maintain. Treasure Data CDP.

Advertising 104

Advertising Interactive Marketing Data Integration 104

AWS Big Data

JULY 28, 2023

Amazon Redshift is a petabyte-scale, enterprise-grade cloud data warehouse service delivering the best price-performance. Today, tens of thousands of customers run business-critical workloads on Amazon Redshift to cost-effectively and quickly analyze their data using standard SQL and existing business intelligence (BI) tools.

Data Lake 69

Data Lake Data Governance Data Warehouse Modeling 69

Alation

APRIL 14, 2022

Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Organizations launched initiatives to be “ data-driven ” (though we at Hired Brains Research prefer the term “data-aware”). On-premises business intelligence and databases. Scheduling.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Jet Global

JULY 17, 2023

One of the major challenges in most business intelligence (BI) projects is data quality (or lack thereof). In fact, most project teams spend 60 to 80 percent of total project time cleaning their data—and this goes for both BI and predictive analytics.

Predictive Analytics 52

Predictive Analytics Reporting Software Strategy 52

O'Reilly on Data

SEPTEMBER 11, 2019

But the database—or, more precisely, the data model —is no longer the sole or, arguably, the primary focus of data engineering. If anything, this focus has shifted to the ML or predictive model. Increasingly, the term “data engineering” is synonymous with the practice of creating data pipelines, usually by hand.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

Jet Global

MAY 1, 2023

Learn how embedded analytics are different from traditional business intelligence and what analytics users expect. Embedded Analytics Definition Embedded analytics are the integration of analytics content and capabilities within applications, such as business process applications (e.g., that gathers data from many sources.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52