Cloudera

JUNE 7, 2023

The revised ZTMM is organized by five categories or pillars: identity, devices, networks, applications and workloads, and data, and four levels of maturity: traditional, initial, advanced, and optimal. Moving to the “optimal” stage of maturity is critical to eliminating unauthorized access by bad actors, both foreign and domestic.

Metadata 79

Metadata Data Lake Optimization Modeling 79

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 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

erwin

OCTOBER 8, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (APIs), file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

AWS Big Data

JUNE 6, 2023

This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 56

Analytics Data Lake Testing Optimization 56

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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 77

Risk Modeling Management Metadata 77

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 92

Data Lake Data Warehouse Metadata Data Architecture 92

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. Moreover, the framework should consume compute resources as optimally as possible per the size of the operational tables.

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Comprehensive search and access to relevant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

JANUARY 15, 2021

Some examples of recent optimizations in Impala include: New multithreading model (see dedicated blog post ). Remote read optimizations: IMPALA-8341: Data cache for remote reads. Impala use of KRPC (see dedicated blog post ). Parquet page indexes (see dedicated blog post ). Benchmark Description.

Data Warehouse 92

Data Warehouse Cost-Benefit Consulting Interactive 92

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. Nominations for the 2021 Cloudera Data Impact Awards are open from now until July 23.

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

erwin

SEPTEMBER 3, 2020

Data governance and EA also provide many of the same benefits of enterprise architecture or business process modeling projects: reducing risk, optimizing operations, and increasing the use of trusted data. Automating Data Governance and Enterprise Architecture.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

AWS Big Data

JUNE 7, 2023

This is a guest blog post co-written with Sumesh M R from Cargotec and Tero Karttunen from Knowit Finland. Through their unique position in ports, at sea, and on roads, they optimize global cargo flows and create sustainable customer value. They are headquartered in Helsinki, Finland, and operates globally in over 100 countries.

Metadata 56

Metadata Data Lake Machine Learning Big Data 56

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. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Metadata Strategy 3.

IT 52

IT Data Lake Strategy Data Science 52

AWS Big Data

JANUARY 8, 2024

Therefore, it is critical for organizations to embrace a low-latency, scalable, and reliable data streaming infrastructure to deliver real-time business applications and better customer experiences. Using a data stream in the middle provides the advantage of using the time series data in other processes and solutions at the same time.

Analytics 111

Analytics IoT Data-driven Snapshot 111

AWS Big Data

MAY 24, 2023

When you build your transactional data lake using Apache Iceberg to solve your functional use cases, you need to focus on operational use cases for your S3 data lake to optimize the production environment. This property is set to true by default. availability.

Data Lake 81

Data Lake Snapshot Metadata Optimization 81

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 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. For CoW tables, queries see the latest data committed.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

Cloudera

NOVEMBER 12, 2020

Burst to Cloud not only relieves pressure on your data center, but it also protects your VIP applications and users by giving them optimal performance without breaking your bank. Today, it is nearly impossible for IT departments to know if a particular workload is optimal to move from on-premises to the cloud.

Data Warehouse 102

Data Warehouse Reporting Risk Cost-Benefit 102

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? One example is the EU’s General Data Protection Regulation (GDPR).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. It brings the reliability and simplicity of SQL tables to big data while enabling engines like Hive, Impala, Spark, Trino, Flink, and Presto to work with the same tables at the same time. Furthermore, it is partitioned on the d_year column.

Snapshot 88

Snapshot Metadata Cost-Benefit Data Warehouse 88

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. For many organizations, however, the question remains, “Is it the right solution for us?” million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 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

AWS Big Data

OCTOBER 4, 2023

Additionally, data owners and data stewards can make data discovery simpler by adding business context to data while balancing access governance to the data via pre-defined approval workflows in the user interface. The metadata forms types, and asset types can be used as templates for defining your assets.

Metadata 100

Metadata Data Lake Publishing Data Governance 100

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 85

Data Lake Metadata Cost-Benefit Data Warehouse 85

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Not only can resources be quickly provisioned and optimized for different workloads and processing needs, but it can be done cost effectively. The Alation Data Catalog will automatically crawl and catalog metadata in your S3 bucket(s).

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

IBM Big Data Hub

JANUARY 18, 2023

A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Value of the data projects are difficult to realize.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

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

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

MARCH 23, 2022

Being multi-function also means integrated end-to-end data pipelines that break siloes, piecing together analytics as a coherent life-cycle where business value can be extracted at each and every stage. Users should be able to choose their tool of choice and take advantage of its workload specific optimizations. 4: Enterprise grade.

Metadata 88

Metadata Data Architecture Machine Learning Cost-Benefit 88

erwin

DECEMBER 17, 2020

Once the organization understands what something is, and it is commonly understood across the enterprise, anyone can build semantically aware reporting and analytical requirements plus deliver a uniform view because there is a common understanding of data. erwin Expands Collaboration with Microsoft.

Modeling 90

Modeling Metadata Data-driven Data Lake 90

Cloudera

NOVEMBER 5, 2020

How do you control data privacy and protect against data breaches when the data is spread across so many different systems? How do you optimize your enterprise-wide infrastructure (mostly cloud) and application expenditures? This is exactly what Cloudera Data Platform (CDP) provides to the Cloudera Data Warehouse.

Data Lake 70

Data Lake Data Warehouse Metadata Optimization 70

AWS Big Data

NOVEMBER 15, 2023

As the organization receives data from multiple external vendors, it often arrives in different formats, typically Excel or CSV files, with each vendor using their own unique data layout and structure. In this blog post, we’ll explore a solution that streamlines this process by leveraging the capabilities of AWS Glue DataBrew.

Metadata 83

Metadata Sales Data Lake Big Data 83

Cloudera

APRIL 22, 2021

Apache Ozone is one of the major innovations introduced in CDP, which provides the next generation storage architecture for Big Data applications, where data blocks are organized in storage containers for larger scale and to handle small objects. Collects and aggregates metadata from components and present cluster state.

Data Lake 98

Data Lake Cost-Benefit Testing Metadata 98

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83