AWS Big Data

DECEMBER 4, 2024

While traditional extract, transform, and load (ETL) processes have long been a staple of data integration due to its flexibility, for common use cases such as replication and ingestion, they often prove time-consuming, complex, and less adaptable to the fast-changing demands of modern data architectures.

Data Integration 113

Data Integration Data Lake Statistics Data-driven 113

IBM Big Data Hub

JANUARY 5, 2023

Poor data quality is one of the top barriers faced by organizations aspiring to be more data-driven. Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues.

Data Architecture 52

Data Architecture Data Quality Strategy Data Lake 52

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 98

Data Lake Analytics Snapshot Data Quality 98

Cloudera

MARCH 28, 2024

But, even with the backdrop of an AI-dominated future, many organizations still find themselves struggling with everything from managing data volumes and complexity to security concerns to rapidly proliferating data silos and governance challenges. The benefits are clear, and there’s plenty of potential that comes with AI adoption.

Data Architecture 94

Data Architecture Strategy Data Lake Data-driven 94

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Previously, there were three types of data structures in telco: .

Data Architecture 84

Data Architecture Cost-Benefit Digital Transformation Business Driver 84

Cloudera

AUGUST 30, 2022

Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Data quality issues deter trust and hinder accurate analytics. Modern data architectures. Deploying modern data architectures. Forrester ). Forrester ).

Data Architecture 79

Data Architecture Data Lake Data Warehouse Metadata 79

AWS Big Data

JANUARY 15, 2025

Need for a data mesh architecture Because entities in the EUROGATE group generate vast amounts of data from various sourcesacross departments, locations, and technologiesthe traditional centralized data architecture struggles to keep up with the demands for real-time insights, agility, and scalability.

IoT 109

IoT Machine Learning Metadata Data-driven 109

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. On the other hand, they don’t support transactions or enforce data quality.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

AWS Big Data

APRIL 8, 2025

In modern data architectures, Apache Iceberg has emerged as a popular table format for data lakes, offering key features including ACID transactions and concurrent write support.

Snapshot 139

Snapshot Management Metadata Big Data 139

CIO Business Intelligence

JANUARY 20, 2023

A big part of preparing data to be shared is an exercise in data normalization, says Juan Orlandini, chief architect and distinguished engineer at Insight Enterprises. Data formats and data architectures are often inconsistent, and data might even be incomplete. They have data swamps,” he says.

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135

AWS Big Data

FEBRUARY 27, 2024

The following are the key components of the Bluestone Data Platform: Data mesh architecture – Bluestone adopted a data mesh architecture, a paradigm that distributes data ownership across different business units. This enables data-driven decision-making across the organization.

Data-driven 109

Data-driven Data Lake Data Quality Data Governance 109

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

AWS Big Data

JANUARY 31, 2023

Data governance is increasingly top-of-mind for customers as they recognize data as one of their most important assets. Effective data governance enables better decision-making by improving data quality, reducing data management costs, and ensuring secure access to data for stakeholders.

Data Lake 98

Data Lake Data Governance Data Architecture Machine Learning 98

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments.

Testing 154

Testing Metadata Dashboards Statistics 154

AWS Big Data

AUGUST 1, 2024

Migrating to Amazon Redshift offers organizations the potential for improved price-performance, enhanced data processing, faster query response times, and better integration with technologies such as machine learning (ML) and artificial intelligence (AI).

Data Warehouse 113

Data Warehouse KPI Optimization Cost-Benefit 113

Data Virtualization

FEBRUARY 28, 2020

Too often the design of new data architectures is based on old principles: they are still very data-store-centric. They consist of many physical data stores in which data is stored repeatedly and redundantly. Over time, new types of data stores,

Data Architecture 52

Data Architecture Data Lake Digital Transformation Data Quality 52

AWS Big Data

JULY 25, 2024

Solution To address the challenge, ATPCO sought inspiration from a modern data mesh architecture. Part 1: Set up account governance and identity management Before you start, compare your current cloud environment, including data architecture, to ATPCO’s environment. Enter a name, such as Sales – Data lake blueprint.

Data Lake 113

Data Lake Metadata Sales Publishing 113

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 83

Data Lake Data Architecture Data-driven Data Warehouse 83

Cloudera

JUNE 13, 2024

After countless open-source innovations ushered in the Big Data era, including the first commercial distribution of HDFS (Apache Hadoop Distributed File System), commonly referred to as Hadoop, the two companies joined forces, giving birth to an entire ecosystem of technology and tech companies.

Big Data 103

Big Data Machine Learning Contextual Data Data Lake 103

Cloudera

DECEMBER 1, 2022

Full-stack observability is a critical requirement for effective modern data platforms to deliver the agile, flexible, and cost-effective environment organizations are looking for. RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises.

Data Quality 84

Data Quality Metrics Data Lake Statistics 84

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 79

Management Metadata Data Architecture Data Lake 79

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 125

Data Warehouse Testing Data Quality Reporting 125

CIO Business Intelligence

JANUARY 30, 2024

Birgit Fridrich, who joined Allianz as sustainability manager responsible for ESG reporting in late 2022, spends many hours validating data in the company’s Microsoft Sustainability Manager tool. Data quality is key, but if we’re doing it manually there’s the potential for mistakes.

Reporting 115

Reporting Data Quality Strategy Data-driven 115

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 101

Data Strategy Strategy Data Warehouse Prescriptive Analytics 101

AWS Big Data

DECEMBER 19, 2024

Data has become an invaluable asset for businesses, offering critical insights to drive strategic decision-making and operational optimization. Delta tables technical metadata is stored in the Data Catalog, which is a native source for creating assets in the Amazon DataZone business catalog.

Data Governance 52

Data Governance Publishing Data-driven Metadata 52

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

CIO Business Intelligence

APRIL 24, 2024

In fact, AMA collects a huge amount of structured and unstructured data from bins, collection vehicles, facilities, and user reports, and until now, this data has remained disconnected, managed by disparate systems and interfaces, through Excel spreadsheets.

Digital Transformation 105

Digital Transformation Business Intelligence Unstructured Data Data Lake 105

CIO Business Intelligence

MAY 21, 2024

Real-Time Intelligence, on the other hand, takes that further by supporting data in AWS, Google Cloud Platform, Kafka installations, and on-prem installations. “We We introduced the Real-Time Hub,” says Arun Ulagaratchagan, CVP, Azure Data at Microsoft. You can monitor and act on the data and you can set thresholds.”

Broadcasting 126

Broadcasting Recreation/Entertainment Manufacturing Data Lake 126

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Analytics 52

Ontotext

APRIL 10, 2024

Bad data tax is rampant in most organizations. Currently, every organization is blindly chasing the GenAI race, often forgetting that data quality and semantics is one of the fundamentals to achieving AI success. Sadly, data quality is losing to data quantity, resulting in “ Infobesity ”. “Any

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

Jedox

OCTOBER 22, 2020

Gartner defines “dark data” as the data organizations collect, process, and store during regular business activities, but doesn’t use any further. Gartner also estimates 80% of all data is “dark”, while 93% of unstructured data is “dark.”.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Alation

NOVEMBER 2, 2022

At Databricks, we’re focused on enabling customers to adopt the data lakehouse, and that’s an open data architecture that combines the best of the data warehouse and the data lake into one platform,” Ferguson says. “[The And data governance is critical to driving adoption.”.

Data Governance 98

Data Governance Marketing Finance Data Lake 98

Peter James Thomas

MAY 3, 2019

Control of Data to ensure it is Fit-for-Purpose. This refers to a wide range of activities from Data Governance to Data Management to Data Quality improvement and indeed related concepts such as Master Data Management. Data Architecture / Infrastructure. Best practice has evolved in this area.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. Data fabric does not replace data warehouses, data lakes, or data lakehouses.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. Only then can you extract insights across fragmented data architecture.

Cost-Benefit 52

Cost-Benefit Data Governance Manufacturing Data Architecture 52

BI-Survey

DECEMBER 22, 2020

Enterprises need a “NEW DEAL” between data producers and data consumers that effectively addresses the top three challenges to improving data handling – time spent, a lack of transparency of data value and insufficient data quality. In addition, their architecture must be made fit for digitalization.

Data-driven 52

Data-driven Data Strategy Strategy Enterprise 52