AWS Big Data

APRIL 29, 2024

It can integrate with external tools for advanced analytics on these audit logs. Ranger Key Management Store (KMS) – Ranger KMS provides encryption and key management, extending Hadoop’s HDFS Transparent Data Encryption (TDE). This provides data security and orderly conduct of daily business operations.

Management 89

Management Big Data Metadata Data Warehouse 89

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 130

Data Architecture Data Warehouse Statistics Visualization 130

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

Ontotext

MAY 2, 2024

Data leaders today are faced with an almost impossible challenge. Particularly those on the “the create side of the house” who are tasked to deliver insights and analytics. Such inconsistencies bring lowered trust in the outcomes analytics and insights leaders try to get. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 109

Analytics IoT Data-driven Snapshot 109

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

AWS Big Data

JANUARY 24, 2024

AWS-powered data lakes, supported by the unmatched availability of Amazon Simple Storage Service (Amazon S3), can handle the scale, agility, and flexibility required to combine different data and analytics approaches. The output will give a count of the number of data and metadata files deleted.

Snapshot 96

Snapshot Data Lake Metadata Optimization 96

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. Iterations of the lakehouse.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Three Types of Metadata in a Data Catalog. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

CIO Business Intelligence

JUNE 23, 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. Iterations of the lakehouse.

Data Lake 88

Data Lake Data Warehouse Machine Learning Cost-Benefit 88

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The script generates a metadata JSON file for each step.

Metadata 76

Metadata Testing Data Lake Consulting 76

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. Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback.

Data Lake 114

Data Lake Data Processing Metadata Snapshot 114

Cloudera

JANUARY 19, 2024

It can help you to create, edit, optimize, fix, and succinctly summarize queries using natural language. This is a real game-changer for data analysts on all levels and will make SQL development faster, easier, and less error-prone. The optimize and the fix functionality do not need user input.

Data Warehouse 71

Data Warehouse Data Processing Optimization Modeling 71

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 55

Analytics Data Lake Testing Optimization 55

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 91

Management Data Warehouse Metrics Dashboards 91

Cloudera

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. You could optimize your table now or at a later stage using the “rewrite_data_files” procedure.

Snapshot 69

Snapshot Metadata Data Warehouse Testing 69

CIO Business Intelligence

NOVEMBER 22, 2022

“Failing to meet these needs means getting left behind and missing out on the many opportunities made possible by advances in data analytics.” The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

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

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. Cloud deployments for suitable workloads gives you the agility to keep pace with rapidly changing business and data needs. You are probably hesitant.

Data Warehouse 101

Data Warehouse Reporting Risk Cost-Benefit 101

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. The Data Catalog provides a central location to govern and keep track of the schema and metadata.

Data Lake 98

Data Lake Sales Data Warehouse Snapshot 98

AWS Big Data

MARCH 29, 2024

Analyzing historical patterns allows you to optimize performance, identify issues proactively, and improve planning. Data Firehose uses an AWS Lambda function to transform data and ingest the transformed records into an Amazon Simple Storage Service (Amazon S3) bucket. In his spare time, he enjoys cycling with his new road bike.

Metrics 101

Metrics Visualization Dashboards Interactive 101

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

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

Timo Elliott

DECEMBER 14, 2022

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. SAP BTP brings together data and analytics, artificial intelligence, application development, automation, and integration in one, unified environment.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

AWS Big Data

APRIL 25, 2024

Additionally, it enables cost optimization by aligning resources with specific use cases, making sure that expenses are well controlled. By isolating workloads with specific security requirements or compliance needs, organizations can maintain the highest levels of data privacy and security. secretsmanager ).

Metadata 94

Metadata Data Processing Management Testing 94

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. All this while the platform serves as the core foundation providing metadata and governance capabilities across these workloads.

Management 42

Management Metadata Analytics Machine Learning 42

Cloudera

SEPTEMBER 17, 2020

To address this, they focused on creating an experimentation-oriented culture, enabled thanks to a cloud-native platform supporting the full data lifecycle. This platform, including an ad-hoc capable data warehouse service with built-in, easy-to-use visualization, made it easy for anyone to jump in and start experimenting.

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

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. DATA FOR GOOD. SECURITY AND GOVERNANCE LEADERSHIP.

Digital Transformation 65

Digital Transformation Machine Learning Optimization Data Lake 65

Sisense

FEBRUARY 17, 2020

Before getting started, you’ll need to grant access to the SNOWFLAKE metadata schema where the ACCOUNT_USAGE tables are. Many data analysts and scientists understand that complex logic may take a while to execute against a database, but a business user expects data to be returned extremely quickly. where query_type = 'SELECT'.

Dashboards 80

Dashboards Data Warehouse Metadata Business Intelligence 80

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes. Industry-wide, the positive ROI on quality data is well understood. 2 – Data profiling. 4 – Data Reporting.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

JUNE 5, 2019

But data alone is not the answer—without a means to interact with the data and extract meaningful insight, it’s essentially useless. Business intelligence (BI) software can help by combining online analytical processing (OLAP), location intelligence, enterprise reporting, and more. Data Mining and Business Intelligence.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. OpenSearch Service provides support for native ingestion from Kinesis data streams or MSK topics.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

Andrew White

OCTOBER 22, 2021

Analytics Tactics (known outcome/known data/BI/analytics v unknown outcome/unknown data/data science/ML) 11. Data Hub Strategy 10. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Integration tactics 4.

IT 52

IT Data Lake Strategy Data Science 52

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97