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 Blog

FEBRUARY 28, 2023

For our joint solution with Snowflake, this means that code-first users can use DataRobot’s hosted Notebooks as the interface and Snowpark processes the data directly in the data warehouse. They can enjoy a hosted experience with code snippets, versioning, and simple environment management for rapid AI experimentation.

Data Processing 72

Data Processing Experimentation Machine Learning Modeling 72

IBM Big Data Hub

NOVEMBER 3, 2023

When you make it easier to work with events, other users like analysts and data engineers can start gaining real-time insights and work with datasets when it matters most. As a result, you reduce the skills barrier and increase your speed of data processing by preventing important information from getting stuck in a data warehouse.

Cost-Benefit 78

Cost-Benefit Experimentation Testing Digital Transformation 78

Sisense

MARCH 6, 2019

Gartner chose to group the rest of the keynote into three main messages according to the following categories: Here are some of the highlights as presented for each of them: Data Driven – “Adopt an Experimental Mindset”. At Sisense we’ve been preaching for BI prototyping and experimentation for quite a while now.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75

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 97

Experimentation Data Lake Uncertainty Enterprise 97

Domino Data Lab

JANUARY 11, 2021

Data Science works best with a high degree of data granularity when the data offers the closest possible representation of what happened during actual events – as in financial transactions, medical consultations or marketing campaign results. Domino Data Lab is the system-of-record for enterprise data science teams.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

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

Cloudera

MARCH 2, 2022

Experimental evaluation: We did extensive evaluation of the technique to see how it affects performance and memory utilization. Now that more and more data warehousing is done in the cloud, much of that in the Cloudera Data Warehouse data service, performance improvement directly equates to cost savings.

Data Warehouse 88

Data Warehouse Optimization Analytics Sales 88

DataKitchen

OCTOBER 5, 2021

Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires. What is DataOps. Low error rates.

Testing 157

Testing Dashboards Measurement Experimentation 157

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 56

IoT Data-driven Data Lake Data Strategy 56

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 64

Data Architecture Metadata Data Lake Snapshot 64

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 100

Metadata Data Lake Publishing Data Governance 100

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. If any of these stages in the lineage changes, it will be captured and can be audited by SDX.

Machine Learning 83

Machine Learning Modeling Metadata Recreation/Entertainment 83

Corinium

APRIL 25, 2019

It definitely depends on the type of data, no one method is always better than the other. For a large volume of structured data, for example, a customer master or data warehouse, where there are many stakeholders in your organization who need to see different subsets, tokenization is generally better.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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 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

Cloudera

NOVEMBER 25, 2020

How could Matthew serve all this data, together , in an easily consumable way, without losing focus on his core business: finding a cure for cancer. The Vision of a Discovery Data Warehouse. A Discovery Data Warehouse is cloud-agnostic. Access to valuable data should not be hindered by the technology.

Data Warehouse 58

Data Warehouse Unstructured Data Analytics Visualization 58

AWS Big Data

MAY 24, 2023

The following examples are also available in the sample notebook in the aws-samples GitHub repo for quick experimentation. You can use either the AWS Glue Data Catalog (recommended) or a Hive catalog for Iceberg tables. Configure Iceberg on a Spark session Configure your Spark session using the %%configure magic command.

Data Lake 81

Data Lake Snapshot Metadata Optimization 81

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 123

Data Lake IT Experimentation Data-driven 123

O'Reilly on Data

OCTOBER 19, 2021

It has far-reaching implications as to how such applications should be developed and by whom: ML applications are directly exposed to the constantly changing real world through data, whereas traditional software operates in a simplified, static, abstract world which is directly constructed by the developer. This approach is not novel.

IT 346

IT Testing Experimentation Software 346

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 Machine Learning Data Science Data-driven 105

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. 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

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. and Google, get a paid solution. LivePerson.

Analytics 135

Analytics Testing Measurement Optimization 135

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

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

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

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. Production Monitoring Only.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Cloudera

JANUARY 11, 2021

How self-service data warehousing frees IT resources. Cloudera Data Warehouse (CDW) is a cloud service and an integral part of the newly released Cloudera Data Platform (CDP). Key features are: Highly scalable and performant open-source engines for BI and data warehousing workloads. Simplified provisioning.

Data Warehouse 62

Data Warehouse Data Lake Cost-Benefit Machine Learning 62

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. .

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

IBM Big Data Hub

SEPTEMBER 25, 2023

They set up a couple of clusters and began processing queries at a much faster speed than anything they had experienced with Apache Hive, a distributed data warehouse system, on their data lake. Data Exploration and Innovation: The flexibility of Presto has encouraged data exploration and experimentation at Uber.

OLAP 94

OLAP Data Lake Data-driven Snapshot 94

Cloudera

MAY 31, 2023

An example would be asking about the price of CDW (Cloudera Data Warehouse), as the language model doesn’t have access to the enterprise price list and standard discount rates the answer will probably provide the typical rates for a collision damage waiver (also abbreviated as CDW), the answer will be factual but out of context.

Enterprise 74

Enterprise Data Processing Experimentation Modeling 74