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. Under Administration , choose Data catalog settings.

Data Lake 93

Data Lake Snapshot Metadata Optimization 93

In(tegrate) the Clouds

JUNE 23, 2016

This week SnapLogic posted a presentation of the 10 Modern Data Integration Platform Requirements on the company’s blog. They are: Application integration is done primarily through REST & SOAP services. Large-volume data integration is available to Hadoop-based data lakes or cloud-based data warehouses.

Data Integration 49

Data Integration Data Lake Data Warehouse Data-driven 49

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. Let’s say that this company is located in Europe and the data product must comply with the GDPR.

Data Lake 103

Data Lake Management Metrics Data Warehouse 103

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 96

Analytics Visualization Data Integration Cost-Benefit 96

AWS Big Data

MAY 18, 2023

It’s even harder when your organization is dealing with silos that impede data access across different data stores. Seamless data integration is a key requirement in a modern data architecture to break down data silos. About the authors Gonzalo Herreros is a Senior Big Data Architect on the AWS Glue team.

Testing 77

Testing Data Lake Cost-Benefit Data Integration 77

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. DeeQu is optimized to run data quality rules in minimal passes that makes it efficient.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

JANUARY 30, 2023

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities. Choose Create role.

Insurance 80

Insurance Data Lake Data-driven Management 80

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

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. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization. The source code for the application is hosted the AWS Glue GitHub.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

erwin

AUGUST 31, 2023

Reduced Data Redundancy : By eliminating data duplication, it optimizes storage and enhances data quality, reducing errors and discrepancies. Efficient Development : Accurate data models expedite database development, leading to efficient data integration, migration, and application development.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

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

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? 11 May 2021. .

Management 80

Management Metadata Data Architecture Data Lake 80

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

BizAcuity

AUGUST 1, 2022

TIBCO Jaspersoft offers a complete BI suite that includes reporting, online analytical processing (OLAP), visual analytics , and data integration. The web-scale platform enables users to share interactive dashboards and data from a single page with individuals across the enterprise. Data Security. Trend Indicators.

Reporting 52

Reporting OLAP Online Analytical Processing Dashboards 52

AWS Big Data

JULY 19, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning, and application development. Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team.

Big Data 83

Big Data Software Consulting Unstructured Data 83

BizAcuity

MAY 16, 2022

To stay relevant in the market and to increase brand awareness, organizations use big data analytics and business intelligence to navigate their way after getting a full understanding of their ideal customers and their behavior before and during the buying journey. So, make sure you have a data strategy in place. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Data modeling: Create relationships between data.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

AWS Big Data

MARCH 29, 2024

Amazon MSK enables us to tailor the data retention duration to our specific requirements, ranging from seconds to unlimited duration. This flexibility grants uninterrupted data availability to our application, which wasn’t possible with our previous architecture.

Cost-Benefit 91

Cost-Benefit Data-driven Metrics Management 91

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

AWS Big Data

JUNE 26, 2023

Companies are faced with the daunting task of ingesting all this data, cleansing it, and using it to provide outstanding customer experience. Typically, companies ingest data from multiple sources into their data lake to derive valuable insights from the data. This will open the ML transforms page.

Insurance 81

Insurance Visualization Data Lake Metrics 81

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. One of the most common use cases for data preparation on Amazon Redshift is to ingest and transform data from different data stores into an Amazon Redshift data warehouse.

Visualization 79

Visualization Data Warehouse Big Data Data Lake 79

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. This is especially helpful when handling massive amounts of big data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Cloudera

JUNE 6, 2019

When a mix of batch, interactive, and data serving workloads are added to the mix, the problem becomes nearly intractable. While this approach provides isolation, it creates another significant challenge: duplication of data, metadata, and security policies, or ‘split-brain’ data lake. Cloudera Manager (CM) 6.2

Metadata 86

Metadata Data Lake Optimization Strategy 86

Cloudera

JUNE 1, 2021

After all, we invented the whole idea of Big Data. So what’s our next big idea? Well, at Cloudera, we envision a world where everyone can quickly and easily access the data-powered information and insights they need – in just a few clicks. . The post Turning the page appeared first on Cloudera Blog.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. As a result, alternative data integration technologies (e.g., CRM platforms). benchmarking study conducted by independent 3rd party ).

Data Processing 92

Data Processing Data Warehouse Enterprise Visualization 92

AWS Big Data

JULY 19, 2023

We show how to perform extract, transform, and load (ELT), an integration process focused on getting the raw data from a data lake into a staging layer to perform the modeling. Data can either be loaded when there is a new sale, or daily; this is where the inserted date or load date comes in handy.

Modeling 69

Modeling Sales Data Warehouse Snapshot 69

Cloudera

FEBRUARY 4, 2019

Stream Processing – Manage and process multiple streams of real-time data using the most advanced distributed stream processing system – Apache Kafka. Process millions of real-time messages per second to feed into your data lake or for immediate streaming analytics.

IoT 73

IoT Prescriptive Analytics Digital Transformation Internet of Things 73

AWS Big Data

MAY 19, 2023

Organizations across all industries have complex data processing requirements for their analytical use cases across different analytics systems, such as data lakes on AWS , data warehouses ( Amazon Redshift ), search ( Amazon OpenSearch Service ), NoSQL ( Amazon DynamoDB ), machine learning ( Amazon SageMaker ), and more.

Machine Learning 83

Machine Learning Metrics Big Data Management 83

Cloudera

MAY 16, 2018

However, in this case, that output is ingested into a data lake. Instead of each group’s tools acting on the output in isolation, they leverage a common visual analytics platform that is native to the lake and uses all of the data without moving it to a separate server. Going Forward: Improved Economics.

Data Lake 42

Data Lake Risk Visualization Unstructured Data 42

AWS Big Data

SEPTEMBER 22, 2023

At Stitch Fix, we have been powered by data science since its foundation and rely on many modern data lake and data processing technologies. In our infrastructure, Apache Kafka has emerged as a powerful tool for managing event streams and facilitating real-time data processing.

Management 103

Management Metrics Cost-Benefit Data Lake 103

Data Virtualization

MARCH 3, 2021

To remain competitive, organizations must have a data management strategy in place to effectively ingest, store, organize, and analyze data while ensuring that it is. The post Data Management Challenges for the Modern Enterprise appeared first on Data Virtualization blog.

Enterprise 75

Enterprise Management Strategy Data Lake 75

AWS Big Data

JULY 12, 2023

This blog post is co-written with Zygimantas Koncius from Etleap. Organizations use their data to extract valuable insights and drive informed business decisions. Amazon Redshift delivers up to five times better price performance than other cloud data warehouses out of the box and helps you keep costs predictable.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

Data Virtualization

OCTOBER 7, 2021

The post Rapidly Enable Tangible Business Value through Data Virtualization (Data minimization) appeared first on Data Virtualization blog.

Digital Transformation 52

Digital Transformation Data Lake Data Warehouse Data Integration 52