Cloudera

OCTOBER 4, 2023

In telecommunications, fast-moving data is essential when we’re looking to optimize the network, improving quality, user satisfaction, and overall efficiency. In financial services, fast-moving data is critical for real-time risk and threat assessments. Kudu has this covered. Ready to stop blinking and never miss a beat?

Data Warehouse 84

Data Warehouse Experimentation Cost-Benefit Dashboards 84

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

Cloudera

MARCH 2, 2022

You can read previous blog posts on Impala’s performance and querying techniques here – “ New Multithreading Model for Apache Impala ”, “ Keeping Small Queries Fast – Short query optimizations in Apache Impala ” and “ Faster Performance for Selective Queries ”. . Analytical SQL workloads use aggregates and joins heavily.

Data Warehouse 86

Data Warehouse Optimization Analytics Sales 86

Domino Data Lab

JULY 2, 2019

In other words, using metadata about data science work to generate code. In this case, code gets generated for data preparation, where so much of the “time and labor” in data science work is concentrated. To build a SQL query, one must describe the data sources involved and the high-level operations (SELECT, JOIN, WHERE, etc.)

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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 Data-driven Machine Learning 66

Occam's Razor

MARCH 23, 2010

My problem with these mistruths and FUD is that they result in a ton of practitioners and companies making profoundly sub optimal choices, which in turn results in not just much longer slogs but also spectacular career implosions and the entire web analytics industry suffering. A majority of web analytics data warehousing efforts fail.

Analytics 118

Analytics Consulting Metrics Experimentation 118

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 20

IoT Big Data Data Warehouse Uncertainty 20