Cloudera

OCTOBER 4, 2023

Flexible use of compute resources on analytics — which is even more important as we start performing multiple different types of analytics, some critical to daily operations and some more exploratory and experimental in nature, and we don’t want to have resource demands collide. Kudu has this covered. appeared first on Cloudera Blog.

Data Warehouse 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

CIO Business Intelligence

NOVEMBER 4, 2022

The company’s multicloud infrastructure has since expanded to include Microsoft Azure for business applications and Google Cloud Platform to provide its scientists with a greater array of options for experimentation. At the data pipeline level, scientists use Apigee, Airflow, NiFi, and Kafka.

Data Lake 124

Data Lake IT Experimentation Data-driven 124

CIO Business Intelligence

AUGUST 23, 2024

Like most enterprises, Bayer’s agricultural division will initially use AWS-based generative AI tools out-of-the-box to automate basic business processes, such as the production of internal technical documentation, McQueen says. Making that available across the division will spur more robust experimentation and innovation, he notes.

Data Science 101

Data Science Experimentation Testing Modeling 101

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. They should also have experience with pattern detection, experimentation in business, optimization techniques, and time series forecasting.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

Occam's Razor

NOVEMBER 5, 2007

For a person such as myself who came from the traditional Data Warehouse and Business Intelligence worlds that was a non-trivial mental model transformation. Experimentation & Testing : Google Website Optimizer, Offermatica, Optimost etc. Competitive Intelligence : Compete, HitWise, Technorati etc.

Analytics 98

Analytics Experimentation Metrics Measurement 98

CIO Business Intelligence

APRIL 6, 2022

We are centered around co-creating with customers and promoting a systematic and scalable innovation approach to solve real-world customers problems—similar to Toyota leveraging Infosys Cobalt to modernize its vehicle data warehouse into a next-generation data lake on AWS. .

Experimentation 103

Experimentation Data Lake Uncertainty Enterprise 103

CIO Business Intelligence

AUGUST 21, 2024

But multiagent AI systems are still in the experimental stages, or used in very limited ways. These AI agents are serving both internal users and clients, says Daniel Avancini, the company’s chief data officer. They use gen AI to interpret complex questions and identify the most relevant data sources.

Risk 136

Risk Insurance Cost-Benefit Software 136

Domino Data Lab

JULY 2, 2019

Of course, if you use several different data management frameworks within your data science workflows—as just about everybody does these days—much of that RDBMS magic vanishes in a puff of smoke. Some may ask: “Can’t we all just go back to the glory days of business intelligence, OLAP, and enterprise data warehouses?”

Metadata 105

Metadata Data Science Machine Learning Data-driven 105

CIO Business Intelligence

APRIL 9, 2025

For many, the level of sophistication can easily range from more sophisticated solutions like Power BI, Tableau, SAP Analytics or IBM Cognos to mid-tier solutions like Domo, Qlik or the tried and true elder statesman for all business analytics consumers, Excel.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

Occam's Razor

MARCH 23, 2010

For big success you'll need to have a Multiplicity strategy: So when you step back and realize at the minimum you'll also have to use one Voice of Customer tool (for qualitative analysis), one Experimentation tool and (if you want to be great) one Competitive Intelligence tool… do you still want to have two clickstream tools?

Analytics 119

Analytics Consulting Metrics Experimentation 119

O'Reilly on Data

SEPTEMBER 11, 2019

Increasingly, the term “data engineering” is synonymous with the practice of creating data pipelines, usually by hand. In quite another respect, however, modern data engineering has evolved to support a range of scenarios that simply were not imaginable 40 years ago. Similarly, “data warehouse” fell 211 places to No.

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

Domino Data Lab

FEBRUARY 4, 2019

We’ll unpack curiosity as a core attribute of effective data science, look at how that informs process for data science (in contrast to Agile, etc.), and dig into details about where science meets rhetoric in data science. That body of work has much to offer the practice of leading data science teams.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

Occam's Razor

FEBRUARY 7, 2011

I have personally had a lot of success using Controlled Experimentation techniques, such as, say, Media Mix Modeling, to understand both current available demand and also segment conversion effectiveness. please refer to the controlled experimentation section, page 205, in the book for more. If you have Web Analytics 2.0 I hope never.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

CIO Business Intelligence

OCTOBER 14, 2024

If a CIO can’t articulate a clear vision of how technology will transform the business, it is unlikely they will inspire their staff. Some CIOs are reluctant to invest in emerging technologies such as AI or machine learning, viewing them as experimental rather than tools for gaining competitive advantage.

Digital Transformation 131

Digital Transformation Experimentation Cost-Benefit Risk 131