Ontotext

APRIL 10, 2024

In most enterprises data teams lack a data map and data asset inventory and are often unaware of data that exists across the organization, its associated profile, quality and associated metadata. Teams can’t access data to build their business use cases. For example, a product data tag is basic metadata.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Data Virtualization

AUGUST 26, 2020

Recently, we have seen the rise of new technologies like big data, the Internet of things (IoT), and data lakes. But we have not seen many developments in the way that data gets delivered. Modernizing the data infrastructure is the.

Data Architecture 59

Data Architecture Internet of Things Data Lake IoT 59

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 124

Data Architecture Data Warehouse Statistics Visualization 124

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 93

Data Lake Data Warehouse Machine Learning Cost-Benefit 93

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. Starting with Amazon EMR release 6.7.0,

Data Lake 82

Data Lake Data Governance Data Architecture Data Warehouse 82

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 79

Data Lake Data Warehouse Machine Learning Cost-Benefit 79

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. All these architecture patterns are integrated with Amazon Kinesis Data Streams.

Analytics 112

Analytics IoT Data-driven Snapshot 112

Cloudera

MARCH 17, 2023

As the use of ChatGPT becomes more prevalent, I frequently encounter customers and data users citing ChatGPT’s responses in their discussions. I love the enthusiasm surrounding ChatGPT and the eagerness to learn about modern data architectures such as data lakehouses, data meshes, and data fabrics.

Unstructured Data 64

Unstructured Data Data Lake Data Warehouse Machine Learning 64

Cloudera

SEPTEMBER 15, 2022

The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms. What is a data fabric?

Data Lake 82

Data Lake Data Architecture Data-driven Data Warehouse 82

Ontotext

NOVEMBER 16, 2023

Figure 1 Shows the overall idea of a data mesh with the major components: What Is a Data Mesh and How Does It Work? Think of data mesh as an operational mode for organizations with a domain-driven, decentralized data architecture. What Is a Data Product and Who Owns Them?

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

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 89

Data Lake Unstructured Data Management Modeling 89

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. Of those tables, some are larger (such as in terms of record volume) than others, and some are updated more frequently than others.

Data Lake 90

Data Lake Data Processing Metadata Snapshot 90

AWS Big Data

AUGUST 31, 2023

Tens of thousands of customers today use Amazon Redshift to analyze exabytes of data and run analytical queries, making it the most widely used cloud data warehouse. 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

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 113

Data Lake Metadata Optimization Statistics 113

AWS Big Data

JUNE 7, 2023

Cargotec captures terabytes of IoT telemetry data from their machinery operated by numerous customers across the globe. This data needs to be ingested into a data lake, transformed, and made available for analytics, machine learning (ML), and visualization.

Metadata 55

Metadata Data Lake Machine Learning Big Data 55

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 66

Data Architecture Metadata Data Lake Snapshot 66

Cloudera

AUGUST 30, 2022

Data quality issues deter trust and hinder accurate analytics. Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Deploying modern data architectures.

Data Architecture 78

Data Architecture Data Lake Metadata Data Warehouse 78

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 87

Data Lake Analytics Snapshot Optimization 87

Cloudera

AUGUST 21, 2020

Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. Data-in-motion on the other hand is data constantly coming into an enterprise or into the cloud that doesn’t have any finite end to it.

Enterprise 62

Enterprise Data Lake Strategy Metadata 62

Alation

FEBRUARY 13, 2020

After coining the term “data catalog,” we were faced with the hard work of explaining exactly what a data catalog is, and why it is critical to achieving business outcomes from self-service analytics. Alation is helping more people than ever make confident data driven decisions. This past year, all of that changed.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

AWS Big Data

JULY 21, 2023

This leads to having data across many instances of data warehouses and data lakes using a modern data architecture in separate AWS accounts. We recently announced the integration of Amazon Redshift data sharing with AWS Lake Formation.

Data Lake 86

Data Lake Data Warehouse Marketing Management 86

AWS Big Data

OCTOBER 25, 2023

But most important of all, the assumed dormant value in the unstructured data is a question mark, which can only be answered after these sophisticated techniques have been applied. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. The solution integrates data in three tiers.

Unstructured Data 118

Unstructured Data Metadata Management Analytics 118

AWS Big Data

NOVEMBER 29, 2023

Since then, customer demands for better scale, higher throughput, and agility in handling a wide variety of changing, but increasingly business critical analytics and machine learning use cases has exploded, and we have been keeping pace. Let’s dive into the highlights.

Data Warehouse 100

Data Warehouse Data Lake Analytics Machine Learning 100

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Analytical and transactional worlds come together.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Cloudera

MARCH 23, 2022

Let’s highlight some of those benefits, and why choosing CDP and Iceberg can future proof your next generation data architecture. . Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1:

Metadata 90

Metadata Data Architecture Machine Learning Cost-Benefit 90

Cloudera

NOVEMBER 17, 2022

The Solution: CDP Private Cloud brings a next-generation hybrid architecture with cloud-native benefits to HBL’s data platform. HBL started their data journey in 2019 when data lake initiative was started to consolidate complex data sources and enable the bank to use single version of truth for decision making.

Management 84

Management Data Lake Consulting Unstructured Data 84

Alation

JULY 7, 2022

In 2013 I joined American Family Insurance as a metadata analyst. I had always been fascinated by how people find, organize, and access information, so a metadata management role after school was a natural choice. The use cases for metadata are boundless, offering opportunities for innovation in every sector.

Metadata 52

Metadata Data-driven Insurance Statistics 52

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI.

Data Lake 99

Data Lake Unstructured Data Data Warehouse Data Quality 99

IBM Big Data Hub

APRIL 27, 2022

Data fabric and data mesh are emerging data management concepts that are meant to address the organizational change and complexities of understanding, governing and working with enterprise data in a hybrid multicloud ecosystem. The good news is that both data architecture concepts are complimentary.

Management 80

Management Metadata Data Architecture Data Lake 80

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 87

Data Lake Data Architecture Metadata Data Warehouse 87

AWS Big Data

JANUARY 22, 2024

Cost and resource efficiency – This is an area where Acast observed a reduction in data duplication, and therefore cost reduction (in some accounts, removing the copy of data 100%), by reading data across accounts while enabling scaling. In this approach, teams responsible for generating data are referred to as producers.

Data-driven 85

Data-driven Advertising Metadata Data Architecture 85

AWS Big Data

JUNE 10, 2024

In this blog post, we dive into different data aspects and how Cloudinary breaks the two concerns of vendor locking and cost efficient data analytics by using Apache Iceberg, Amazon Simple Storage Service (Amazon S3 ), Amazon Athena , Amazon EMR , and AWS Glue.

Data Lake 108

Data Lake Metadata Snapshot Analytics 108

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. Monitoring Job Metadata.

Testing 152

Testing Metadata Dashboards Statistics 152

Alation

APRIL 14, 2022

And, as organizations progress and grow, “data drift” starts to impact data usage, models, and your business. In today’s AI/ML-driven world of data analytics, explainability needs a repository just as much as those doing the explaining need access to metadata, EG, information about the data being used.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

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 84

Enterprise Data Warehouse Data Lake Optimization 84

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68