Domino Data Lab

JULY 22, 2019

Paco Nathan presented, “Data Science, Past & Future” , at Rev. At Rev’s “ Data Science, Past & Future” , Paco Nathan covered contextual insight into some common impactful themes over the decades that also provided a “lens” help data scientists, researchers, and leaders consider the future.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. A data warehouse is one of the components in a data hub.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 129

Data Architecture Data Warehouse Statistics Visualization 129

O'Reilly on Data

JANUARY 29, 2019

In other words, could we see a roadmap for transitioning from legacy cases (perhaps some business intelligence) toward data science practices, and from there into the tooling required for more substantial AI adoption? Data scientists and data engineers are in demand.

Deep Learning 208

Deep Learning Machine Learning Data Science Metadata 208

Andrew White

DECEMBER 9, 2019

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. Modern data (and analytics) governance does not necessarily need: Wall-to-wall discovery of your data and metadata.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

Timo Elliott

JANUARY 6, 2022

The data you’ve collected and saved over the years isn’t free. If storage costs are escalating in a particular area, you may have found a good source of dark data. Analyze your metadata. If you’ve yet to implement data governance, this is another great reason to get moving quickly. Data analysis and exploration.

IT 133

IT Metadata Data-driven Data Governance 133

Alation

FEBRUARY 20, 2020

Today, we’re excited to announce that Salesforce is bringing the collaborative power of data cataloging to its users with the integration of Einstein Analytics and the Alation Data Catalog. Alation’s Data Catalog makes finding, understanding and verifying data to ultimately uncover true business insights easy.

Metadata 52

Metadata Analytics Dashboards Sales 52

DataKitchen

JANUARY 5, 2021

Remote working has revealed the inconsistency and fragility of workflow processes in many data organizations. The data teams share a common objective; to create analytics for the (internal or external) customer. Data Science Workflow – Kubeflow, Python, R. Data Engineering Workflow – Airflow, ETL.

Testing 147

Testing Data Governance Metadata Visualization 147

Rocket-Powered Data Science

MARCH 10, 2020

I wrote an extensive piece on the power of graph databases, linked data, graph algorithms, and various significant graph analytics applications. I publish this in its original form in order to capture the essence of my point of view on the power of graph analytics. Well, the graph analytics algorithm would notice!

Metadata 250

Metadata Machine Learning ROI Prescriptive Analytics 250

Rocket-Powered Data Science

FEBRUARY 15, 2023

Most of these rules focus on the data, since data is ultimately the fuel, the input, the objective evidence, and the source of informative signals that are fed into all data science, analytics, machine learning, and AI models. The latter is essential for Generative AI implementations.

Strategy 290

Strategy Experimentation Uncertainty Machine Learning 290

CIO Business Intelligence

MAY 24, 2022

Some of the accelerators included as part of the new platform are integrations with Salesforce, NPI data, National Patient Account Services, Workday, Oracle Fusion HCM Cloud, Orange HRM, Salesforce Health Cloud, MedPro, healthcare-focused cloud company Veeva, and HR vendor UltiPro. Analytics for faster decision making.

Finance 133

Finance Management Metadata Data Quality 133

O'Reilly on Data

JANUARY 8, 2019

Beyond investments in narrowing the skills gap, companies are beginning to put processes in place for their data science projects, for example creating analytics centers of excellence that centralize capabilities and share best practices. Continuing investments in (emerging) data technologies.

IoT 204

IoT Machine Learning Internet of Things Data Science 204

IBM Big Data Hub

OCTOBER 4, 2022

This includes capturing of the metadata, tracking provenance and documenting the model lifecycle. The ability to track and share model facts and documentation across the organization provides backup for analytic decisions. Having this backup is crucial when addressing stakeholder, customers and concerns from regulators.

Metadata 100

Metadata Risk Risk Management Experimentation 100

Smart Data Collective

APRIL 5, 2022

The data science profession has become highly complex in recent years. Data science companies are taking new initiatives to streamline many of their core functions and minimize some of the more common issues that they face. IBM Watson Studio is a very popular solution for handling machine learning and data science tasks.

Cost-Benefit 122

Cost-Benefit Machine Learning Data Science Unstructured Data 122

Rocket-Powered Data Science

JULY 6, 2021

This is accomplished through tags, annotations, and metadata (TAM). granules) of the data collection for fast search, access, and retrieval is also important for efficient orchestration and delivery of the data that fuels AI, automation, and machine learning operations. Collect, curate, and catalog (i.e.,

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267

CIO Business Intelligence

MARCH 24, 2023

The program must introduce and support standardization of enterprise data. Programs must support proactive and reactive change management activities for reference data values and the structure/use of master data and metadata. One of its key capabilities, TrustCheck, provides real-time “guardrails” to workflows.

Data Governance 142

Data Governance Management Metadata Data Quality 142

Cloudera

OCTOBER 11, 2022

Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. But it isn’t just aggregating data for models. Data needs to be prepared and analyzed. And that data is likely in clouds, in data centers and at the edge.

Snapshot 89

Snapshot Data Science Digital Transformation Metadata 89

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 56

Analytics Data Lake Testing Optimization 56

DataKitchen

AUGUST 9, 2021

In essence, a domain is an integrated data set and a set of views, reports, dashboards, and artifacts created from the data. The domain also includes code that acts upon the data, including tools, pipelines, and other artifacts that drive analytics execution.

Testing 246

Testing Data Lake Metadata Publishing 246

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Management 42

Management Metadata Analytics Machine Learning 42

Rita Sallam

APRIL 2, 2023

We explored these questions and more at our Bake-Offs and Show Floor Showdowns at our Data and Analytics Summit in Orlando with 4,000 of our closest D&A friends and family. The Show Floor Showdowns were held on the Exhibit Hall show floor and were based on the same demo script and data set used in the Bake-Offs.

Optimization 52

Optimization Machine Learning Insurance Risk 52

Octopai

MAY 31, 2022

The ultimate data organizational tool, letting any data user in your organization easily see what data assets you have and all the pertinent details about them, is a data catalog. Bonus tool: active metadata management. An active metadata management tool adds a maître d’ to self-serve analytics.

Management 52

Management Metadata Business Intelligence ROI 52

CIO Business Intelligence

NOVEMBER 22, 2022

“Unique insights derived from an organization’s data constitute a competitive advantage that’s inherent to their business and not easily copied by competitors,” she observes. Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.”

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Alation

AUGUST 30, 2022

Centralization of metadata. A decade ago, metadata was everywhere. Consequently, useful metadata was unfindable and unusable. We had data but no data intelligence and, as a result, insights remained hidden or hard to come by. This universe of metadata represents a treasure trove of connected information.

Metadata 52

Metadata Data Quality Data Governance Machine Learning 52

Alation

FEBRUARY 20, 2020

Prior to the Big Data revolution, companies were inward-looking in terms of data. During this time, data-centric environments like data warehouses dealt only with data created within the enterprise. THE NEED FOR METADATA TOOLS. Given the characteristics of data acquisition, how should it be handled?

Metadata 52

Metadata IT Data Governance Data Warehouse 52

Alation

FEBRUARY 13, 2020

Data curation is a term that has recently become a common part of data management vocabulary. Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. Who Are the Data Curators? What about Data Stewards? What’s Next?

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? I spent the majority of my time helping clients decide which was the right Hadoop platform and which NoSQL / nonrelational data store to pick for specific use cases. This is the focus of my latest research which published in Jan 2019. I am glad you asked.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

CDW Research Hub

APRIL 17, 2019

Splunk recently released a security eBook to help companies understand the challenges and action steps to a security program that utilizes data to stay ahead of attacks. Here is a breakdown of the suggested six stages of the Analytics-Driven Security Journey, so you can get started on your voyage. Stage 1: Collection.

Analytics 40

Analytics Data-driven Machine Learning Metadata 40

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It also lets you choose the right engine for the right workload at the right cost, potentially reducing your data warehouse costs by optimizing workloads. Track models and drive transparent processes.

Risk 74

Risk Modeling Management Metadata 74

Cloudera

JUNE 7, 2022

Also, Cloudera DataFlow is rated highly in the GigaOm Radar for Streaming Data Platforms. Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform.

IT 106

IT Data Architecture Unstructured Data Big Data 106

Analytics Vidhya

JANUARY 27, 2022

This article was published as a part of the Data Science Blogathon. A centralized location for research and production teams to govern models and experiments by storing metadata throughout the ML model lifecycle. A Metadata Store for MLOps appeared first on Analytics Vidhya. Keeping track of […].

Metadata 143

Metadata Machine Learning Data Science Publishing 143

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

APRIL 19, 2023

The solution generates a list of data products, product attributes, and the associated probability scores to show join ability. We use Valentine, a data science algorithm for comparing datasets, to improve data product recommendations. The data science algorithm Valentine is an effective tool for this.

Technology 85

Technology Data-driven Machine Learning Sales 85

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Delta Lake added transaction support to the data in a lake. Iterations of the lakehouse.

Data Lake 86

Data Lake Data Warehouse Machine Learning Cost-Benefit 86

CIO Business Intelligence

JUNE 23, 2022

Also, Cloudera DataFlow is rated highly in the GigaOm Radar for Streaming Data Platforms. Leading industry analysts rated Cloudera better at analytic and operational data use cases than many well-known cloud vendors. Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform.

IT 79

IT Data Architecture Unstructured Data Big Data 79

Cloudera

AUGUST 31, 2021

Data warehousing is the backbone of every data driven organization , providing mission critical analytics. Today, modern data warehousing has evolved to meet the intensive demands of the newest analytics required for a business to be data driven. Copyright © 2021 Accenture. All rights reserved.

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. Data lakes and data warehouses unify large volumes and varieties of data into a central location.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89