Cloudera

JUNE 7, 2022

Want to manage and analyze data of all types including machine, structured, transactional, and unstructured – anywhere? Only Cloudera has the power to span multi-cloud and on-premises with a hybrid data platform. That’s where modern data architectures like data lakehouse, data fabric and data mesh come in.

IT 110

IT Unstructured Data Data Architecture Government 110

Cloudera

FEBRUARY 7, 2019

With the right technology now in place, ATB Financial is landing and curating more data than ever to bring data-driven insights to the business and its customers. Implementing a Modern Data Architecture. Reducing Analytic Time to Value by More Than 90 Percent. Check out our customer stories.

Utilities 65

Utilities Big Data Google Cloud Data Analytics 65

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. Third-generation – more or less like the previous generation but with streaming data, cloud, machine learning and other (fill-in-the-blank) fancy tools. See the pattern?

Pharmaceutical 98

Pharmaceutical Data Lake Data Architecture Scala 98

Snowflake

DECEMBER 18, 2023

To help spotlight the expanding role of the Chief Data Officer and others with similar responsibilities, Snowflake has identified 50 individuals who we believe exemplify the qualities necessary to advance the data, analytics and AI agenda responsibly.

Transportation 80

Transportation Insurance Data Architecture Technology 80

Snowflake

DECEMBER 18, 2023

To help spotlight the expanding role of the Chief Data Officer and others with similar responsibilities, Snowflake has identified 50 individuals who we believe exemplify the qualities necessary to advance the data, analytics and AI agenda responsibly.

Transportation 76

Transportation Insurance Data Architecture Technology 76

Data Engineering Weekly

APRIL 28, 2024

The platform's structure allows for detailed tracking and analysis of CPU, memory, I/O, and job lifecycle metrics, facilitating proactive management and optimization of data processes. These architectures are designed to handle massive amounts of data by defining how data moves through systems from ingestion to processing to storage.

Data Engineering 52

Data Engineering Data Engineer Engineering Hospitality 52

Databand.ai

AUGUST 30, 2023

DataOps Architecture: 5 Key Components and How to Get Started Ryan Yackel August 30, 2023 What Is DataOps Architecture? DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Cloudera

OCTOBER 19, 2022

The telecommunications industry continues to develop hybrid data architectures to support data workload virtualization and cloud migration. Telco organizations are planning to move towards hybrid multi-cloud to manage data better and support their workforces in the near future. 2- AI capability drives data monetization.

Cloud 78

Cloud Telecommunication Data Governance Government 78

DataKitchen

NOVEMBER 29, 2021

Data Gets Meshier. 2022 will bring further momentum behind modular enterprise architectures like data mesh. The data mesh addresses the problems characteristic of large, complex, monolithic data architectures by dividing the system into discrete domains managed by smaller, cross-functional teams.

Data Lake 98

Data Lake Manufacturing Architecture Data Architecture 98

Cloudera

OCTOBER 11, 2022

Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. Different data types need different types of analytics – real-time, streaming, operational, data warehouses. And that data is likely in clouds, in data centers and at the edge.

Data Science 92

Data Science Aggregated Data Data Consulting 92

Cloudera

NOVEMBER 1, 2022

In the private sector, excluding highly regulated industries like financial services, the migration to the public cloud was the answer to most IT modernization woes, especially those around data, analytics, and storage. It’s here where the private cloud delivers.

Cloud 87

Cloud Government Cloud Computing Data Architecture 87

DataKitchen

SEPTEMBER 17, 2021

The following section will explore the DataOps-enabled data mesh in more depth. It would be incredibly inefficient to build a data mesh without automation. DataOps focuses on automating data analytics workflows to enable rapid innovation with low error rates. Conclusion.

Architecture 94

Architecture Data Architecture Raw Data Government 94

Snowflake

JANUARY 19, 2023

Vikrant Bhan, Group Head Analytics, Data and Integration, Nestlé Yuta Hishinuma , CTO, Chura Data Inc. Vikrant Bhan, Group Head Analytics, Data and Integration, Nestlé Yuta Hishinuma , CTO, Chura Data Inc.

Data 108

Data Data Governance Data Architecture Government 108

Data Engineering Weekly

MARCH 3, 2024

The migration enhanced data quality, lineage visibility, performance improvements, cost reductions, and better reliability and scalability, setting a robust foundation for future expansions and onboarding.

Data Engineering 67

Data Engineering Data Engineer Pipeline-centric Engineering 67

Cloudera

JANUARY 5, 2023

We have been working with APAC organizations to operationalize data analytics and AI solutions to unlock data-driven decision-making and operational efficiency, with them quickly seeing distinct business benefits. They also address the concerns of IT teams in allowing access to organizational data. .

Banking 52

Banking Machine Learning Insurance Data Architecture 52

Knowledge Hut

MARCH 13, 2024

Every big company is either eager to implement big data analytics into their business strategies or has already incorporated it into their systems. These large volumes of data are helpful for companies in any sector as nowadays, user data shares equal importance in a company alongside its profits and market share.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 13, 2024

Every big company is either eager to implement big data analytics into their business strategies or has already incorporated it into their systems. These large volumes of data are helpful for companies in any sector as nowadays, user data shares equal importance in a company alongside its profits and market share.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Knowledge Hut

MARCH 28, 2024

They work together with stakeholders to get business requirements and develop scalable and efficient data architectures. Role Level Advanced Responsibilities Design and architect data solutions on Azure, considering factors like scalability, reliability, security, and performance.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

DataKitchen

DECEMBER 30, 2020

In June of 2020, Database Trends & Applications featured DataKitchen’s end-to-end DataOps platform for its ability to coordinate data teams, tools, and environments in the entire data analytics organization with features such as meta-orchestration , automated testing and monitoring , and continuous deployment : DataKitchen [link].

Manufacturing 96

Manufacturing Big Data Data Pipeline Data Science 96

Monte Carlo

NOVEMBER 22, 2022

SeatGeek’s data challenges How SeatGeek improved data quality at scale Results of implementing data observability The future of data at SeatGeek SeatGeek’s data landscape As an online ticketing marketplace with distributed business intelligence needs, data quality plays a big part in SeatGeek’s day-to-day operations.

Data 52

Data BI Business Intelligence Data Architecture 52

DataKitchen

JUNE 12, 2023

The DataOps Manifesto is a useful set of principles to guide your understanding of these powerful, grounded, industry-spanning ideas on improving technical team productivity, delivery quality, and cycle time in data analytics. So today, another fundamental idea needs to be defined and given the manifesto treatment: the Data Journey.

ETL Tools 52

ETL Tools Data Science Data Lake Hadoop 52

Knowledge Hut

JUNE 23, 2023

Go for the best courses for Data Engineering and polish your big data engineer skills to take up the following responsibilities: You should have a systematic approach to creating and working on various data architectures necessary for storing, processing, and analyzing large amounts of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

Teradata

OCTOBER 21, 2020

Two major forces impacting IT are on a collision course: the desire for a “modern data architecture” and businesses' need for data analytics. Find out more.

Architecture 52

Architecture Data Architecture Data Analytics IT 52

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Analytics tell the story of markets and customers. Analytics enable companies to understand their environment. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving.

Engineering 59

Engineering Manufacturing Data Analytics Data Workflow 59

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

Cloudera

APRIL 13, 2021

CDP addresses the high multi-tenancy, contention isolation, and workload demands of the company’s largest customer use cases—all while enabling the company to find and implement unique data analytics products and services. Its existing data architecture, however, wasn’t up for the gig.

Cloud 76

Cloud Pharmaceutical Medical Data Warehouse 76

Precisely

MARCH 14, 2023

Then, data clouds from providers like Snowflake and Databricks made deploying and managing enterprise-grade data solutions much simpler and more cost-effective. Now, almost any company can build a solid, cost-effective data analytics or BI practice grounded in these new cloud platforms. Bigger, better results.

Data Integration 52

Data Integration High Quality Data BI Data 52

Cloudera

MARCH 17, 2023

Align everything to corporate strategy I lead data and analytics at Cloudera. We’re called Cloudera Data Analytics (CDA). Best Practices for Data Products” #HybridCloud with Sanjeev Mohan (Analyst, SanjoMo) and Luke Roquet (Cloudera) on Tuesday, March 21, 11a in Swan Ballroom 4, WDW Swan Hotel. How very clever.

Data Architecture 80

Data Architecture Data Architecture Data Analytics 80

Cloudera

SEPTEMBER 24, 2021

In the network itself, 5G, IoT and Edge architectures were being designed with copious ‘information services’, and network virtualization was on the cusp of being production grade. All of these network changes were designed with data in mind – and the data architectures needed to be ready to cater for them.

Data Architect 94

Data Architect Government NoSQL Big Data 94

Cloudera

NOVEMBER 18, 2020

The technological linchpin of its digital transformation has been its Enterprise Data Architecture & Governance platform. It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery. times more effective than traditional mass marketing.

Medical 121

Medical Banking Telecommunication Government 121

Knowledge Hut

NOVEMBER 28, 2023

This increased the data generation and the need for proper data storage requirements. A data architect is concerned with designing, creating, deploying, and managing a business entity's data architecture. Skills As the certification is significant, skills are the one that matters the most it.

Data Architect 52

Data Architect Data Science Certification Big Data 52

Cloudera

NOVEMBER 17, 2022

The bank will be able to secure, manage, and analyse huge volumes of structured and unstructured data, with the analytic tool of their choice. . Smooth, hassle-free deployment in just six weeks. See other customers’ success here .

Banking 84

Banking Management Data Lake Professional Services 84

AltexSoft

MAY 12, 2023

Data lakes offer a flexible and cost-effective approach for managing and storing unstructured data, ensuring high durability and availability. Amazon S3 , as the data lake storage platform, enables organizations to store, analyze, and manage big data workloads, including backup and archiving. Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

SEPTEMBER 26, 2021

Becoming a Big Data Engineer - The Next Steps Big Data Engineer - The Market Demand An organization’s data science capabilities require data warehousing and mining, modeling, data infrastructure, and metadata management. Most of these are performed by Data Engineers.

Big Data 52

Big Data Data Engineering Data Engineer Engineering 52

Silectis

JANUARY 22, 2021

In this demo, we’ll show you how native tools in the Magpie data engineering platform play well with Snowflake, ultimately, allowing your team to do more in a centralized data engineering environment. This is an important piece of a modern and reliable data architecture.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Data Engineering Podcast

SEPTEMBER 3, 2021

There has been a lot of conversation recently about different interpretations of the "modern data stack" For a team who is just starting to build out their platform, how much credence should they be giving to those debates? How do you measure the success of a data platform? How do you measure the success of a data platform?

Designing 100

Designing Building SQL BI 100