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.

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Data Lake Data Processing Metadata Snapshot 93

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 55

Metadata Data Lake Machine Learning Big Data 55

Cloudera

FEBRUARY 14, 2024

Introduction Apache Iceberg has recently grown in popularity because it adds data warehouse-like capabilities to your data lake making it easier to analyze all your data — structured and unstructured. Expiring snapshots is a relatively cheap operation and uses metadata to determine newly unreachable files.

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Strategy Optimization Snapshot Metadata 57

AWS Big Data

JUNE 15, 2023

In today’s world, customers manage vast amounts of data in their Amazon Simple Storage Service (Amazon S3) data lakes, which requires convoluted data pipelines to continuously understand the changes in the data layout and make them available to consuming systems. Review and update the crawler settings.

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Data Lake Metadata Cost-Benefit Management 90

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. For InitialRunFlag , choose Setup.

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Data Lake Data Transformation Cost-Benefit Data-driven 88

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.

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Data Lake Snapshot Metadata Optimization 95

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).

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Data Lake ROI Metadata Cost-Benefit 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.

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Data Lake Metadata Data Warehouse Data Governance 52

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.

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Data Lake Metadata Cost-Benefit Data Warehouse 79

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.

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Snapshot Metadata Cost-Benefit Data Warehouse 90

AWS Big Data

JANUARY 17, 2024

With Amazon EMR 6.15, we launched AWS Lake Formation based fine-grained access controls (FGAC) on Open Table Formats (OTFs), including Apache Hudi, Apache Iceberg, and Delta lake. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

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Data Lake Snapshot Big Data Data-driven 96

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?

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Data Processing Metadata Broadcasting Statistics 143

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 81

Metadata Data Lake Optimization Modeling 81

AWS Big Data

NOVEMBER 22, 2023

Today, we’re making available a new capability of AWS Glue Data Catalog that allows generating column-level statistics for AWS Glue tables. These statistics are now integrated with the cost-based optimizers (CBO) of Amazon Athena and Amazon Redshift Spectrum , resulting in improved query performance and potential cost savings.

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Statistics Data Lake Optimization Data-driven 103

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.

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Data Lake Data Warehouse Machine Learning Cost-Benefit 92

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.

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Data Lake Data Warehouse Metadata Optimization 72

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.

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Data Lake Cost-Benefit Testing Metadata 100

AWS Big Data

NOVEMBER 29, 2023

We have seen a strong customer demand to expand its scope to cloud-based data lakes because data lakes are increasingly the enterprise solution for large-scale data initiatives due to their power and capabilities. The team uses dbt-glue to build a transformed gold model optimized for business intelligence (BI).

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Data Lake Management Metrics Data Warehouse 105

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.

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Data Governance Metadata Testing Data Lake 145

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

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 102

Metadata Data Lake Publishing Data Governance 102

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!

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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.

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Metadata Sales Data Lake Big Data 86

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.

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Data Lake Data Warehouse Data-driven Metadata 52

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.

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Modeling Metadata Data-driven Data Lake 90

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.

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Metadata Machine Learning Unstructured Data Data Lake 100

Cloudera

JUNE 16, 2022

Organizations are increasingly building low-latency, data-driven applications, automations, and intelligence from real-time data streams. Cloudera Stream Processing (CSP) enables customers to turn streams into data products by providing capabilities to analyze streaming data for complex patterns and gain actionable intel.

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Data Lake Manufacturing Metadata Dashboards 86

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.

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Cost-Benefit Metadata Data Governance Modeling 78

Cloudera

DECEMBER 16, 2022

Notably, these same services simplify repatriating data workloads back to private clouds, to save on cloud infrastructure expenses. Cloudera is closely partnered with the leading cloud service providers (CSPs), and has optimized our platform and services to run as efficiently on their infrastructure services as possible.

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Management Metadata Machine Learning Data Lake 90

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 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging. With Netezza support for 1.2

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Cost-Benefit Metadata Optimization Management 77

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.

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Analytics Data Lake Testing Optimization 55

erwin

AUGUST 31, 2023

It delivers the ability to capture and unify the business and technical perspectives of data assets, enables effective collaboration between a variety of stakeholders, and delivers metadata-driven automation to accelerate the creation and maintenance of data sources on virtually any data management platform. Save My Spot!

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Data-driven Modeling Enterprise Structured Data 98

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 92

Data Lake Cost-Benefit Data-driven Dashboards 92

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?

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Machine Learning Data Warehouse Modeling Cost-Benefit 63

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.

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Data Quality Data Architecture Strategy Data Lake 52

Cloudera

APRIL 3, 2023

In this blog, we will share with you in detail how Cloudera integrates core compute engines including Apache Hive and Apache Impala in Cloudera Data Warehouse with Iceberg. We will publish follow up blogs for other data services. Iceberg basics Iceberg is an open table format designed for large analytic workloads.

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Data Warehouse Snapshot Metadata Cost-Benefit 81