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

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. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

Risk 71

Risk Modeling Management Metadata 71

AWS Big Data

JUNE 6, 2023

This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. Unless, of course, the rest of their data also resides in the Google Cloud. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data. It consists of full-day and intraday tables.

Analytics 55

Analytics Data Lake Testing Optimization 55

Andrew White

OCTOBER 22, 2021

If you follow my blog for any period of time you will know that for most years I have attended our annual Gartner IT Symposium I do a day-in-the-life blog of an analyst. Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10.

IT 52

IT Data Lake Strategy Data Science 52

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. Data for Enterprise AI: E xperian BIS — Improving the accuracy of commercial data aggregation with data science and machine learning. INDUSTRY TRANSFORMATION.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Andrew White

MARCH 22, 2019

I have blogged before (see this from 2014: A Day in the Life of an Analyst” at Gartner’s IT/Expo Symposium – Day 3 ) about the hot topics I discussed with attendees at our Symposia and data and analytics conferences. Your Future Requires You to Define Your Real Master Data. Age maybe against us. Let’s start with the first.

Analytics 68

Analytics Metadata Data Governance Management 68

Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. In times of potentially troublesome change, the apparent paradox and inner poetry of these.

Data Warehouse 98

Data Warehouse ROI Data Integration Internet of Things 98

Data Virtualization

JUNE 22, 2023

The Denodo Platform is a logical data management platform, powered by. The post Denodo Joins Forces with Presto appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration 52

Data Integration Management Data Lake Metadata 52

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Data Virtualization

NOVEMBER 17, 2022

The idea seems, on the face of it, easy to understand: a data catalog is simply a centralized inventory of the data assets within an organization. Data catalogs also seek to be the. The post Choosing a Data Catalog: Data Map or Data Delivery App?

Data Integration 59

Data Integration Management Data Lake IT 59

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 78

Data Lake Metadata Cost-Benefit Data Warehouse 78

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 80

Data Architecture Data Lake Metadata Data Warehouse 80

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 brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Data Ingestion.

Machine Learning 138

Machine Learning Data Science Data Lake Modeling 138

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 80

Metadata Data Warehouse Snapshot Data Quality 80

Smart Data Collective

AUGUST 5, 2021

This means that the process would die in the middle of the final writes, making consumers distinctly read the input data frames. In this blog, we will cover an overview of Delta Lakes , its advantages, and how the above challenges can be overcome by moving to Delta Lake and migrating to Spark 3.0 What is Delta Lake?

Data Processing 143

Data Processing Metadata Broadcasting Statistics 143

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. 2 “Exposing The Data Mesh Blind Side ” Forrester.

Management 80

Management Metadata Data Architecture Data Lake 80

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 94

Data Lake Data Warehouse IT Analytics 94

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 82

Data Warehouse Data Transformation Testing Data Lake 82

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 103

Metadata Machine Learning Unstructured Data Data Lake 103

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

IBM Big Data Hub

JULY 17, 2023

In this blog, I will cover: What is watsonx.ai? sales conversation summaries, insurance coverage, meeting transcripts, contract information) Generate: Generate text content for a specific purpose, such as marketing campaigns, job descriptions, blogs or articles, and email drafting support. What capabilities are included in watsonx.ai?

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

IBM Big Data Hub

MAY 9, 2023

Optimized for all data, analytics and AI workloads, watsonx.data combines the flexibility of a data lake with the performance of a data warehouse, helping businesses to scale data analytics and AI anywhere their data resides. Savings may vary depending on configurations, workloads and vendors.

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

Alation

SEPTEMBER 23, 2021

What Is a Data Catalog? A data catalog is a centralized storage bank of metadata on information sources from across the enterprise, such as: Datasets. The data catalog also stores metadata (data about data, like a conversation), which gives users context on how to use each asset. Visualizations.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

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. . Let’s Talk!

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 45

Big Data Data Lake Internet of Things Enterprise 45

Cloudera

JUNE 16, 2022

CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. The DevOps/app dev team wants to know how data flows between such entities and understand the key performance metrics (KPMs) of these entities. She is a smart data analyst and former DBA working at a planet-scale manufacturing company.

Data Lake 88

Data Lake Manufacturing Metadata Dashboards 88

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 96

Data Lake Cost-Benefit Data-driven Dashboards 96

IBM Big Data Hub

JULY 5, 2023

Data Lakes have been around for well over a decade now, supporting the analytic operations of some of the largest world corporations. Such data volumes are not easy to move, migrate or modernize. The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale.

Data Lake 61

Data Lake Metadata Cost-Benefit Data Warehouse 61

Alation

FEBRUARY 17, 2023

This past week, I had the pleasure of hosting Data Governance for Dummies author Jonathan Reichental for a fireside chat , along with Denise Swanson , Data Governance lead at Alation. Can you differentiate between governance of raw data and enhanced data (information)? Establishing a solid vision and mission is key.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52