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 124

Big Data Data Analytics Analytics Predictive Modeling 124

Domino Data Lab

OCTOBER 14, 2020

Experimentation and collaboration are built into the core of the platform. This ability enhances the efficiency of operational management and optimizes the cost of experimentation. Our scientists and teams are familiar with working in Spark on EMR and using data with our existing feature store and data warehouse.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

DataRobot

JANUARY 20, 2022

As health and care delivery converges, analytical staff will be required to work across more boundaries with larger volumes of data than ever before. . Snowflake and DataRobot AI Cloud unique no-code user interfaces democratize the building of datasets, models, and accessing valuable business insights in a timely manner.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

IBM Big Data Hub

SEPTEMBER 25, 2023

With a few taps on a mobile device, riders request a ride; then, Uber’s algorithms work to match them with the nearest available driver and calculate the optimal price. Uber’s prowess as a transportation, logistics and analytics company hinges on their ability to leverage data effectively. But the simplicity ends there.

OLAP 88

OLAP Data Lake Data-driven Snapshot 88

Cloudera

JANUARY 28, 2022

As I meet with our customers, there are always a range of discussions regarding the use of the cloud for financial services data and analytics. Customers vary widely on the topic of public cloud – what data sources, what use cases are right for public cloud deployments – beyond sandbox, experimentation efforts.

Slice and Dice 113

Slice and Dice Cost-Benefit Risk Data Governance 113

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation.

Data Lake 87

Data Lake Snapshot Metadata Optimization 87

AWS Big Data

JANUARY 24, 2023

This post explains how to create a design that automatically backs up Amazon Simple Storage Service (Amazon S3), the AWS Glue Data Catalog, and Lake Formation permissions in different Regions and provides backup and restore options for disaster recovery. He specializes in migrating enterprise data warehouses to AWS Modern Data Architecture.

Data Architecture 68

Data Architecture Metadata Data Lake Snapshot 68

AWS Big Data

NOVEMBER 14, 2023

However, in many organizations, data is typically spread across a number of different systems such as software as a service (SaaS) applications, operational databases, and data warehouses. Such data silos make it difficult to get unified views of the data in an organization and act in real time to derive the most value.

IoT 55

IoT Data-driven Data Lake Data Strategy 55

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 102

Metadata Data Lake Publishing Data Governance 102

Cloudera

FEBRUARY 16, 2022

This allows data scientists, engineers and data management teams to have the right level of access to effectively perform their role. By logging the performance of every combination of search parameters within an experiment, we can choose the optimal set of parameters when building a model.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

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

Corinium

APRIL 25, 2019

Most enterprises in the 21st century regard data as an incredibly valuable asset – Insurance is no exception - to know your customers better, know your market better, operate more efficiently and other business benefits. It definitely depends on the type of data, no one method is always better than the other.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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

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

OCTOBER 19, 2010

If after rigorous analysis you have determined that you have evolved to a stage that you need a data warehouse then you are out of luck with Yahoo! If you can show ROI on a DW it would be a good use of your money to go with Omniture Discover, WebTrends Data Mart, Coremetrics Explore. Google Website Optimizer.

Analytics 135

Analytics Testing Measurement Optimization 135

Occam's Razor

NOVEMBER 5, 2007

The fact that to make optimal decisions on the web I was going to have to be comfortable with multiple sources of data, all valuable and all necessary to win. The strategy, for me, was two fold: Go figure out what sources of data, web and non-web, were needed to make decisions. It was totally worth it.

Analytics 98

Analytics Experimentation Metrics Measurement 98

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

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 or non-U.S.),

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

Occam's Razor

MAY 18, 2010

, don't allow you to do on the fly segmentation of all your data (not without asking you to change javascript script tags every time you need to segment something, or not without paying extra or paying for additional "data warehouse" solutions). Segment Category #3: Outcomes.

Analytics 123

Analytics Key Performance Indicator Metrics Measurement 123