IBM Big Data Hub

NOVEMBER 28, 2022

Metadata management performs a critical role within the modern data management stack. However, as data volumes continue to grow, manual approaches to metadata management are sub-optimal and can result in missed opportunities. This puts into perspective the role of active metadata management. Improve data discovery.

Metadata 56

Metadata Data Quality Data-driven Data Governance 56

Cloudera

NOVEMBER 13, 2020

This is part of our series of blog posts on recent enhancements to Impala. Impala Optimizations for Small Queries. We’ll discuss the various phases Impala takes a query through and how small query optimizations are incorporated into the design of each phase. The entire collection is available here. Query Planner Design.

Optimization 142

Optimization Metadata Statistics Cost-Benefit 142

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. An AWS Glue job (metadata exporter) runs daily on the source account.

Metadata 59

Metadata Data Lake Machine Learning Big Data 59

Ontotext

FEBRUARY 16, 2023

Ontotext’s approach is to optimize models and algorithms through human contribution and benchmarking in order to create better and more accurate AI. You can read more about it in this blog post. What Are The Benefits Of Using Ontotext Metadata Studio? Ontotext Metadata Studio addresses all of these problems head on.

Metadata 59

Metadata Measurement Metrics Modeling 59

Cloudera

FEBRUARY 14, 2024

This blog discusses a few problems that you might encounter with Iceberg tables and offers strategies on how to optimize them in each of those scenarios. A bloated metadata.json file could increase both read/write times because a large metadata file needs to be read/written every time. Iceberg doesn’t delete the old data files.

Strategy 59

Strategy Optimization Snapshot Metadata 59

Alation

MARCH 2, 2023

With lots of data comes yet more calls for automation, optimization, and productivity initiatives to put that data to good use. Analysis, however, requires enterprises to find and collect metadata. Download Gartner’s “Market Guide for Active Metadata Management” to learn more, or read on for a summary of the firm’s outlook.

Metadata 52

Metadata Marketing IT Data Quality 52

AWS Big Data

SEPTEMBER 11, 2024

This blog post is co-written with Hardeep Randhawa and Abhay Kumar from HPE. Each file arrives as a pair with a tail metadata file in CSV format containing the size and name of the file. This metadata file is later used to read source file names during processing into the staging layer.

Data Architecture 91

Data Architecture Optimization Data Warehouse Metadata 91

IBM Big Data Hub

DECEMBER 18, 2023

Achieving consistently high performance requires an efficient routing system, optimizing traffic between the services your application depends on. In summary, IBM NS1 Connect offers a range of traffic steering options to meet diverse business needs to help ensure optimal application performance in the “now” era.

Optimization 69

Optimization Metadata Metrics Management 69

Cloudera

JULY 10, 2024

In the public cloud, these cost management issues are compounded by consumption rates, where compute is often overused due to a lack of visibility into optimization opportunities. The data temperature feature lets us see whether hot or cold data sets are deployed optimally, including the underlying file sizes and partitioning styles.

Cost-Benefit 97

Cost-Benefit Metadata Optimization Measurement 97

AWS Big Data

MARCH 22, 2024

When you use Trino on Amazon EMR or Athena, you get the latest open source community innovations along with proprietary, AWS developed optimizations. and Athena engine version 2, AWS has been developing query plan and engine behavior optimizations that improve query performance on Trino. Starting from Amazon EMR 6.8.0

Metadata 100

Metadata Statistics Broadcasting Optimization 100

Cloudera

DECEMBER 21, 2023

Some are returning errors that are difficult to find—and if you’re missing KPIs you have to fix, optimize, and measure every bit of code, which can take a considerable amount of time and trial and error. Optimizing any query Sometimes we are looking at a query that just seems overly complex. What a nightmare!

Optimization 66

Optimization Sales Data Warehouse Measurement 66

AWS Big Data

JUNE 10, 2024

Cloudinary is a cloud-based media management platform that provides a comprehensive set of tools and services for managing, optimizing, and delivering images, videos, and other media assets on websites and mobile applications. This concept makes Iceberg extremely versatile.

Data Lake 118

Data Lake Metadata Snapshot Analytics 118

Cloudera

APRIL 18, 2024

Artificial intelligence (AI) is something that, by its very nature, can be surrounded by a sea of skepticism but also excitement and optimism when it comes to harnessing its power. Preparing For an AI-powered Future There’s plenty of optimism and interest surrounding GenAI and AI more broadly.

Analytics 109

Analytics Metadata Data Strategy Optimization 109

Cloudera

NOVEMBER 15, 2024

Optimized for analytics: Iceberg tables are designed to deliver analytics faster and more effectively. The metadata-driven approach ensures quick query planning so defenders don’t have to deal with slow processes when they need fast answers. Real-Time Threat Detection with Iceberg Cyber log data is massive and constantly evolving.

Analytics 83

Analytics Metadata Snapshot Data-driven 83

Cloudera

FEBRUARY 8, 2024

Overview This blog post describes support for materialized views for the Iceberg table format. Queries containing joins, filters, projections, group-by, or aggregations without group-by can be transparently rewritten by the Hive optimizer to use one or more eligible materialized views.

Snapshot 89

Snapshot Metadata Cost-Benefit Data Warehouse 89

AWS Big Data

NOVEMBER 22, 2024

How RFS works OpenSearch and Elasticsearch snapshots are a directory tree that contains both data and metadata. Metadata files exist in the snapshot to provide details about the snapshot as a whole, the source cluster’s global metadata and settings, each index in the snapshot, and each shard in the snapshot.

Snapshot 52

Snapshot Metadata Recreation/Entertainment Data Processing 52

Rita Sallam

APRIL 2, 2023

Are there mitigation strategies that show reasons for optimism? We also gave the demo script and data set to all vendors in the Exhibit Hall to create demos for their booths and to submit for this blog. The results showing the impact of flooding, predictions for the future and reasons for optimism were fascinating.

Optimization 52

Optimization Machine Learning Insurance Risk 52

Cloudera

JULY 19, 2023

It is a replicated, highly-available service that is responsible for managing the metadata for all objects stored in Ozone. In this blog post, we will highlight the work done recently to improve the performance of Ozone Manager to scale to exabytes of data. The hardware specifications are included at the end of this blog.

Management 69

Management Metadata Metrics Optimization 69

DataKitchen

AUGUST 16, 2024

Data Pipeline Observability: Optimizes pipelines by monitoring data quality, detecting issues, tracing data lineage, and identifying anomalies using live and historical metadata. At DataKitchen, we think of this is a ‘meta-orchestration’ of the code and tools acting upon the data.

Marketing 126

Marketing Data Quality Testing Metadata 126

Cloudera

JANUARY 15, 2021

Pushing down column predicate filters to Kudu allows for optimized execution by skipping reading column values for filtered out rows and reducing network IO between a client, like the distributed query engine Apache Impala, and Kudu. One of the ways Apache Kudu achieves this is by supporting column predicates with scanners. Join Queries.

Optimization 72

Optimization Broadcasting Testing Metadata 72

Cloudera

NOVEMBER 15, 2024

Optimized for analytics: Iceberg tables are designed to deliver analytics faster and more effectively. The metadata-driven approach ensures quick query planning so defenders don’t have to deal with slow processes when they need fast answers. Real-Time Threat Detection with Iceberg Cyber log data is massive and constantly evolving.

Analytics 59

Analytics Metadata Snapshot Data-driven 59

AWS Big Data

MARCH 2, 2023

Apache Iceberg is an open table format for very large analytic datasets, which captures metadata information on the state of datasets as they evolve and change over time. Apache Iceberg addresses customer needs by capturing rich metadata information about the dataset at the time the individual data files are created.

Data Lake 122

Data Lake Data Processing Metadata Snapshot 122

Ontotext

JUNE 27, 2019

These series of blog posts review some of its new features and functionalities. GraphDB: MongoDB Document Store Integration for Large-scale Metadata Management. For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information.

Metadata 40

Metadata Management Enterprise Publishing 40

Smart Data Collective

AUGUST 5, 2021

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 Along with the ability to implement ACID transactions and scalable metadata handling, Delta Lakes can also unify the streaming and batch data processing”. .

Data Processing 143

Data Processing Metadata Broadcasting Statistics 143

AWS Big Data

NOVEMBER 22, 2023

Hudi provides tables , transactions , efficient upserts and deletes , advanced indexes , streaming ingestion services , data clustering and compaction optimizations, and concurrency control , all while keeping your data in open source file formats. Read optimized queries – For MoR tables, queries see the latest data compacted.

Data Lake 102

Data Lake Snapshot Metadata Optimization 102

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. Update your-iceberg-storage-blog in the following configuration with the bucket that you created to test this example.

Data Lake 87

Data Lake Snapshot Metadata Optimization 87

Cloudera

JULY 24, 2024

Cloudera helps you with this maintenance by delivering improvements and vulnerability patches in Service Packs and Cumulative Hotfixes (CHFs) < Cumulative Hotfix Blog > Although applying Service Packs and CHFs is a straightforward process, you do need to restart services. To learn more, visit our product page.

Metadata 77

Metadata Optimization Management IT 77

Cloudera

JULY 13, 2023

In this blog, we will discuss performance improvement that Cloudera has contributed to the Apache Iceberg project in regards to Iceberg metadata reads, and we’ll showcase the performance benefit using Apache Impala as the query engine. The data files and metadata files in Iceberg format are immutable.

Metadata 69

Metadata Snapshot Data Warehouse Statistics 69

IBM Big Data Hub

JANUARY 17, 2023

At the core of a data lakehouse architecture includes the storage, metadata service and the query engine, and typically a data governance component made up of a policy engine and a data dictionary. Furthermore, metadata defining the table format may also be stored with the file. A word on managed services.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

FEBRUARY 22, 2022

Companies such as Adobe , Expedia , LinkedIn , Tencent , and Netflix have published blogs about their Apache Iceberg adoption for processing their large scale analytics datasets. . Users do not need to know how the table is partitioned to optimize the SQL query performance. Multi-function analytics .

Snapshot 108

Snapshot Metadata Cost-Benefit Data Architecture 108

Cloudera

SEPTEMBER 15, 2022

There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. Retail, where big data is used across all stages of the retail process—from product development, pricing, demand forecasting, and for inventory optimization in the stores.

Metadata 86

Metadata Big Data Optimization Unstructured Data 86

Ontotext

JUNE 27, 2019

For example, it’s data generated as a result of text mining algorithms that includes document metadata attributes and annotations with links to the first type of information. Optimizing for speed. Let’s optimize this query, so that we still fetch particular mentions from GraphDB, but specify only the data that we want to work with.

Metadata 40

Metadata Management Optimization Enterprise 40

AWS Big Data

MAY 28, 2024

It’s the preferred choice to run big data workloads because it helps improve throughput and optimize Amazon EC2 spend. and higher support using the Data Catalog as a metadata store for streaming and batch SQL workflows. Amazon EMR on EKS natively integrates tools and functionalities to enable these—and more.

Data Processing 101

Data Processing Cost-Benefit Metadata Optimization 101

erwin

JUNE 26, 2020

Organizations with particularly deep data stores might need a data catalog with advanced capabilities, such as automated metadata harvesting to speed up the data preparation process. The most optimal and streamlined way to achieve this is by using a data catalog, which can provide a first stop for users ahead of working in BI platforms.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

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

Smart Data Collective

MAY 11, 2023

Bhaval Patel of Space-O Technologies wrote a blog post about the growing importance of AI for mobile apps. In this blog post, we will explore how AI-driven app development strategies can help your e-commerce business stay ahead in the mobile-first world. AI has been invaluable for e-commerce brands.

Cost-Benefit 101

Cost-Benefit Optimization Data-driven Machine Learning 101

IBM Big Data Hub

OCTOBER 4, 2023

Also, a lakehouse can introduce definitional metadata to ensure clarity and consistency, which enables more trustworthy, governed data. Watsonx.data enables users to access all data through a single point of entry, with a shared metadata layer deployed across clouds and on-premises environments. All of this supports the use of AI.

Data Lake 77

Data Lake Metadata Data Warehouse Cost-Benefit 77