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. On data warehouses and data lakes.

Data Lake 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

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. An AI governance framework ensures the ethical, responsible and transparent use of AI and machine learning (ML). Capture and document model metadata for report generation.

Risk 70

Risk Modeling Management Metadata 70

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. SECURITY AND GOVERNANCE LEADERSHIP. INDUSTRY TRANSFORMATION. Last, but certainly not least.

Digital Transformation 69

Digital Transformation Machine Learning Optimization Data Lake 69

Alation

FEBRUARY 13, 2020

Data curation is important in today’s world of data sharing and self-service analytics, but I think it is a frequently misused term. When speaking and consulting, I often hear people refer to data in their data lakes and data warehouses as curated data, believing that it is curated because it is stored as shareable data.

Metadata 52

Metadata Data Warehouse Data Lake Data Governance 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Domino Data Lab

APRIL 3, 2019

The top three items are essentially “the devil you know” for firms which want to invest in data science: data platform, integration, data prep. Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. Rinse, lather, repeat.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. Data Ingestion.

Machine Learning 137

Machine Learning Data Science Data Lake Modeling 137

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

AWS Big Data

OCTOBER 25, 2023

By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data. After decades of digitizing everything in your enterprise, you may have an enormous amount of data, but with dormant value. The solution integrates data in three tiers.

Unstructured Data 118

Unstructured Data Metadata Management Analytics 118

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lake 77

Data Lake Metadata Cost-Benefit Data Warehouse 77

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Warehouse, data lake convergence. Meet the data lakehouse.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Only metadata will be regenerated. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Metadata management .

Metadata 79

Metadata Data Warehouse Snapshot Data Quality 79

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

Domino Data Lab

AUGUST 8, 2019

Paco Nathan ‘s latest monthly article covers Sci Foo as well as why data science leaders should rethink hiring and training priorities for their data science teams. In this episode I’ll cover themes from Sci Foo and important takeaways that data science teams should be tracking. Introduction.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

IBM Big Data Hub

APRIL 27, 2022

Gartner defines a data fabric as “a design concept that serves as an integrated layer of data and connecting processes. The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. What’s a data mesh?

Management 79

Management Metadata Data Architecture Data Lake 79

Cloudera

OCTOBER 7, 2022

Cloudera’s mission, values, and culture have long centered around using open source engines on open data and table formats to enable customers to build flexible and open data lakes. To date, dbt was only available on proprietary cloud data warehouses, with very little interoperability between different engines.

Data Warehouse 80

Data Warehouse Data Transformation Testing Data Lake 80

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Cloudera

JANUARY 21, 2021

With CDW, as an integrated service of CDP, your line of business gets immediate resources needed for faster application launches and expedited data access, all while protecting the company’s multi-year investment in centralized data management, security, and governance. Proprietary file formats mean no one else is invited in!

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” Iceberg handles massive data born in the cloud.

Metadata 102

Metadata Machine Learning Unstructured Data Data Lake 102

IBM Big Data Hub

JULY 17, 2023

is our enterprise-ready next-generation studio for AI builders, bringing together traditional machine learning (ML) and new generative AI capabilities powered by foundation models. Automated development: Automates data preparation, model development, feature engineering and hyperparameter optimization using AutoAI.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

IBM Big Data Hub

MAY 9, 2023

After some impressive advances over the past decade, largely thanks to the techniques of Machine Learning (ML) and Deep Learning , the technology seems to have taken a sudden leap forward. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

Alation

APRIL 14, 2022

In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used. The Cloud Data Migration Challenge. Pushing data to a data lake and assuming it is ready for use is shortsighted.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

AWS Big Data

MARCH 26, 2024

This can be achieved using AWS Entity Resolution , which enables using rules and machine learning (ML) techniques to match records and resolve identities. Then, you transform this data into a concise format. The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

AWS Big Data

APRIL 26, 2024

IAM Identity Center now supports trusted identity propagation , a streamlined experience for users who require access to data with AWS analytics services. AWS Lake Formation allows data administrators to centrally govern, secure, and share data for analytics and machine learning (ML). Choose Grant.

Analytics 94

Analytics Data Lake Management Enterprise 94

AWS Big Data

JUNE 10, 2024

This amalgamation empowers vendors with authority over a diverse range of workloads by virtue of owning the data. This authority extends across realms such as business intelligence, data engineering, and machine learning thus limiting the tools and capabilities that can be used.

Data Lake 108

Data Lake Metadata Snapshot Analytics 108

AWS Big Data

FEBRUARY 2, 2023

Since its launch in 2006, Amazon Simple Storage Service (Amazon S3) has experienced major growth, supporting multiple use cases such as hosting websites, creating data lakes, serving as object storage for consumer applications, storing logs, and archiving data. This could be your data lake or application S3 bucket.

Reporting 87

Reporting Data Lake Management Optimization 87

Cloudera

AUGUST 21, 2020

Over time, additional use cases and functions expanded from original EDW and Data Lake related functions to support increasing demands from the business. More sources, data, and functionality were added to these platforms, expanding their value but adding to the complexity, such as: Streaming data ingestion. .

Cost-Benefit 76

Cost-Benefit Big Data ROI Risk 76

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 94

Data Lake Cost-Benefit Data-driven Dashboards 94

bridgei2i

MARCH 3, 2021

Also, ML-ops or machine learning operationalization approaches to bridge the gap between sandbox and production pipelines, while ensuring model lifecycle management from raw data to predictive, as well as prescriptive, insights integration. Pavan: Really fascinating discussion, Prinkan. Signing off. Stay home, stay safe.

Enterprise 98

Enterprise Digital Transformation Data-driven Interactive 98

AWS Big Data

JULY 14, 2023

In this post, we discuss how the Amazon Finance Automation team used AWS Lake Formation and the AWS Glue Data Catalog to build a data mesh architecture that simplified data governance at scale and provided seamless data access for analytics, AI, and machine learning (ML) use cases.

Finance 83

Finance Metadata Big Data Recreation/Entertainment 83

Andrew White

JANUARY 11, 2021

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52