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. In other cases, it’s more of a standard computational requirement and we help them provide the data in the right formats.

Data Lake 115

Data Lake IT Experimentation Data-driven 115

CIO Business Intelligence

JUNE 14, 2023

The certification focuses on the seven domains of the analytics process: business problem framing, analytics problem framing, data, methodology selection, model building, deployment, and lifecycle management. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 125

Big Data Data Analytics Analytics Predictive Modeling 125

Cloudera

SEPTEMBER 17, 2020

A large oil and gas company was suffering over not being able to offer users an easy and fast way to access the data needed to fuel their experimentation. To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle.

Experimentation 81

Experimentation Data Warehouse Dashboards Visualization 81

Domino Data Lab

OCTOBER 14, 2020

We’ve developed a model-driven software platform, called Climate FieldView , that captures, visualizes, and analyzes a vast array of data for farmers and provides new insight and personalized recommendations to maximize crop yield. For example, our models can show farmers how to increase their production while using less fertilizer.

Experimentation 99

Experimentation Modeling Deep Learning Testing 99

DataRobot

JANUARY 20, 2022

— Collaborating via Snowflake Data Cloud and DataRobot AI Cloud Platform will enable multiple organizations to build a community movement where experimentation, innovation, and creativity flourish. Looking forward through data. Grasping the digital opportunity.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

DataRobot Blog

FEBRUARY 28, 2023

Integrating different systems, data sources, and technologies within an ecosystem can be difficult and time-consuming, leading to inefficiencies, data silos, broken machine learning models, and locked ROI. Model Deployment Customers need the flexibility to deploy models into different environments.

Data Processing 72

Data Processing Experimentation Machine Learning Modeling 72

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. Meta-Orchestration . Production Monitoring Only.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Domino Data Lab

JANUARY 11, 2021

Arming data science teams with the access and capabilities needed to establish a two-way flow of information is one critical challenge many organizations face when it comes to unlocking value from their modeling efforts. Domino integrates with Snowflake to solve this challenge by providing a modern approach to data.

Recreation/Entertainment 103

Recreation/Entertainment Data Science Data Warehouse Modeling 103

Cloudera

AUGUST 2, 2018

Data teams in these insurance firms are leading the charge in rebuilding entire business models around data and analytics. In each of the cases outlined above, the technology enabler is a new generation of data warehouses. We call it ‘Modern Data Warehousing’. The key ingredient is something we call H-3.

Data Warehouse 51

Data Warehouse Insurance Experimentation Software 51

Cloudera

MAY 31, 2023

Riding the wave of the generative AI revolution, third party large language model (LLM) services like ChatGPT and Bard have swiftly emerged as the talk of the town, converting AI skeptics to evangelists and transforming the way we interact with technology. Adding Enterprise Context to LLMs Contextual Limitation is not unique to enterprises.

Enterprise 74

Enterprise Data Processing Experimentation Modeling 74

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 75

Cost-Benefit Experimentation Testing Digital Transformation 75

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

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

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

CIO Business Intelligence

APRIL 6, 2022

The race to embrace digital technologies to compete and stay relevant in emerging business models is compelling organizations to shift focus. This model helps iterate rapid innovation, failing fast and learning from those failures by sourcing direct feedback from end users.

Experimentation 86

Experimentation Data Lake Uncertainty Enterprise 86

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

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. Their product is the data.

Testing 152

Testing Dashboards Measurement Experimentation 152

IBM Big Data Hub

SEPTEMBER 25, 2023

Uber’s DNA as an analytics company At its core, Uber’s business model is deceptively simple: connect a customer at point A to their destination at point B. For traditional analytics, they are bringing data discipline to their use of Presto. They ingest data in snapshots from operational systems.

OLAP 89

OLAP Data Lake Data-driven Snapshot 89

Corinium

APRIL 25, 2019

Then you can be more confident you’re protecting that data in the right way, in the right places, via protection policies that keep it safe without getting in the way of the business getting value from that data. The protection policy follows the data. This is a much more proactive and scalable model.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

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

Domino Data Lab

JULY 2, 2019

Paco Nathan ‘s latest article covers program synthesis, AutoPandas, model-driven data queries, and more. In other words, using metadata about data science work to generate code. Using ML models to search more effectively brought the search space down to 102—which can run on modest hardware. Introduction.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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

O'Reilly on Data

SEPTEMBER 11, 2019

2 in frequency in proposal topics; a related term, “models,” is No. Terms that relate to data engineering, data management, and data analytics dominate the top tiers of proposal topics. An ML-related topic, “models,” was No. For example, even though ML and ML-related concepts —a related term, “ML models,” (No.

IoT 20

IoT Big Data Data Warehouse Uncertainty 20

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. I have already presented my mental model for Web Analytics 2.0. Experimentation & Testing : Google Website Optimizer, Offermatica, Optimost etc.

Analytics 98

Analytics Experimentation Metrics Measurement 98

Occam's Razor

FEBRUARY 7, 2011

The best option is to hire a statistician with experience in data modeling and forecasting. Brian Krick: Best way to measure and communicate "available demand" from available channels (social, search, display) for forecast modeling. because the data is so very not available. Please see the advice above.

Analytics 94

Analytics Measurement Metrics Predictive Analytics 94

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