Ascend.io

NOVEMBER 14, 2024

Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. In this blog post, we’ll explore key strategies for future-proofing your data pipelines.

Data Pipeline 52

Data Pipeline Amazon Web Services Data Integration Data 52

DataKitchen

NOVEMBER 5, 2024

The Race For Data Quality In A Medallion Architecture The Medallion architecture pattern is gaining traction among data teams. It is a layered approach to managing and transforming data. By systematically moving data through these layers, the Medallion architecture enhances the data structure in a data lakehouse environment.

Architecture 78

Architecture Raw Data Pipeline-centric Data Ingestion 78

Striim

NOVEMBER 17, 2023

Striim serves as a real-time data integration platform that seamlessly and continuously moves data from diverse data sources to destinations such as cloud databases, messaging systems, and data warehouses, making it a vital component in modern data architectures.

Machine Learning 52

Machine Learning Data Process PostgreSQL Process 52

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

Striim

JANUARY 17, 2025

Striim Cloud is designed to support these needs by offering fully managed, real-time data streaming pipelines, allowing organizations to build and scale data processing workflows in minutes.

Healthcare 52

Healthcare Google Cloud Government Data Validation 52

Hevo

AUGUST 16, 2024

This blog explores the world of open source data orchestration tools, highlighting their importance in managing and automating complex data workflows. From Apache Airflow to Google Cloud Composer, we’ll walk you through ten powerful tools to streamline your data processes, enhance efficiency, and scale your growing needs.

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Google Cloud Data Workflow Data Data Engineering 52

Maxime Beauchemin

FEBRUARY 28, 2017

Astronomer’s DataRouter builds upon it as a service for data pipelines from any source to any destination. You can learn more about how Astronomer uses Apache Airflow and our open source philosophy in recent blog posts.

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Data Engineering Data Engineer Engineering Data Pipeline 130

Confluent

OCTOBER 10, 2019

Confluent Platform and Confluent Cloud are already used in many IoT deployments, both in Consumer IoT and Industrial IoT (IIoT). Most scenarios require a reliable, scalable, and secure end-to-end integration that enables bidirectional communication and data processing in real time. But that doesn’t move much.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20

Cloudera

SEPTEMBER 30, 2022

With DFF, users now have the choice of deploying NiFi flows not only as long-running auto scaling Kubernetes clusters but also as functions on cloud providers’ serverless compute services including AWS Lambda, Azure Functions, and Google Cloud Functions.

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Google Cloud AWS Cloud Cloud Storage 73

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Reflow — A system for incremental data processing in the cloud. Azure DevOps.

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Consulting Machine Learning Data Science Data Pipeline 120

Knowledge Hut

DECEMBER 22, 2023

Benefits: Cost Efficiency Scalability Increased Developer Productivity Simplified Deployment and Management Examples: Building serverless APIs and microservices using serverless platforms like AWS Lambda, Azure Functions, or Google Cloud Functions. We go over the most essential future trends in this blog.

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Entertainment Machine Learning Utilities Google Cloud 105

Knowledge Hut

APRIL 25, 2023

Here, we'll take a look at the top data engineer tools in 2023 that are essential for data professionals to succeed in their roles. These tools include both open-source and commercial options, as well as offerings from major cloud providers like AWS, Azure, and Google Cloud. What are Data Engineering Tools?

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Cloudera

DECEMBER 15, 2022

With CDP, customers can deploy storage, compute, and access, all with the freedom offered by the cloud, avoiding vendor lock-in and taking advantage of best-of-breed solutions. The post Implement a Multi-Cloud Open Lakehouse with Apache Iceberg in Cloudera Data Platform appeared first on Cloudera Blog.

Cloud 80

Cloud Metadata Data Warehouse Google Cloud 80

ProjectPro

SEPTEMBER 6, 2021

Are you confused about choosing the best cloud platform for your next data engineering project ? AWS vs. GCP blog compares the two major cloud platforms to help you choose the best one. So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud?

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AWS Amazon Web Services Google Cloud Cloud Storage 52

ProjectPro

JANUARY 24, 2023

Tired of relentlessly searching for the most effective and powerful data warehousing solutions on the internet? This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. Search no more!

Bytes 52

Bytes Google Cloud Data Warehouse Cloud Storage 52

Cloudera

MARCH 14, 2023

We just announced the general availability of Cloudera DataFlow Designer , bringing self-service data flow development to all CDP Public Cloud customers. In our previous DataFlow Designer blog post , we introduced you to the new user interface and highlighted its key capabilities.

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Data Pipeline Designing Kafka Metadata 84

Edureka

FEBRUARY 12, 2023

You should also have a good understanding of cloud computing and be familiar with at least one cloud platform, such as AWS, Google Cloud, or Microsoft Azure. Google Cloud Platform (GCP): GCP provides a wide range of services, including computing, storage, database, security, and more.

Engineering 52

Engineering Amazon Web Services Programming Language Google Cloud 52

Data Engineering Weekly

FEBRUARY 12, 2023

But compute needs will likely not change much over time; most analysis is done over recent data. Historical data processing is a rare event, where 99% of the computing happens over the last 24 hours of data. The blog definitely added to my curiosity to think more. There is a lot of truth in this statement.

Data Engineering 52

Data Engineering Data Engineer Engineering Hadoop 52

Cloudera

JANUARY 12, 2021

Cloudera provides its customers with a set of consistent solutions running on-premises and in the cloud to ensure customers are successful in their data journey for all of their use cases, regardless of where they are deployed. So, the public cloud is not always a good fit for every business needs.

Cloud 52

Cloud Google Cloud Government BI 52

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? Why Are Data Engineering Skills In Demand? Don’t worry!

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Certification Data Engineering Data Engineer Engineering 52

Databand.ai

DECEMBER 13, 2022

He also has more than 10 years of experience in big data, being among the few data engineers to work on Hadoop Big Data Analytics prior to the adoption of public cloud providers like AWS, Azure, and Google Cloud Platform. Deepak regularly shares blog content and similar advice on LinkedIn.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Knowledge Hut

DECEMBER 4, 2023

Mind map helps you grasp the core topics though a cloud computing concept map and helps you understand how those concepts fit together. Let us explore more about cloud computing and mind maps through this blog. These elements differentiate cloud technology from the traditional system and are a factor in its rapid growth.

Cloud Computing 52

Cloud Computing Cloud Google Cloud AWS 52

Knowledge Hut

JULY 24, 2023

In this blog, we will talk about the future of database management. Get ready to discover fascinating insights, uncover mind-boggling facts, and explore the transformative potential of cutting-edge technologies like blockchain, cloud computing, and artificial intelligence. Examples include Amazon DynamoDB and Google Cloud Datastore.

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Database NoSQL Management Relational Database 52

Monte Carlo

JUNE 2, 2024

These languages are used to write efficient, maintainable code and create scripts for automation and data processing. Databases and Data Warehousing: Engineers need in-depth knowledge of SQL (88%) and NoSQL databases (71%), as well as data warehousing solutions like Hadoop (61%).

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Monte Carlo

JUNE 2, 2024

These languages are used to write efficient, maintainable code and create scripts for automation and data processing. Databases and Data Warehousing: Engineers need in-depth knowledge of SQL (88%) and NoSQL databases (71%), as well as data warehousing solutions like Hadoop (61%).

Engineering 52

Engineering Amazon Web Services Data Science AWS 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. Contents: What is the role of an Azure Data Engineer? Azure data engineers are essential in the design, implementation, and upkeep of cloud-based data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

DECEMBER 21, 2023

To boost database performance, data engineers also update old systems with newer or improved versions of current technology. As a data engineer, a strong understanding of programming, databases, and data processing is necessary. Read blogs, attend webinars, and take online courses.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

dbt Developer Hub

NOVEMBER 22, 2022

Once your data warehouse is built out, the vast majority of your data will have come from other SaaS tools, internal databases, or customer data platforms (CDPs). Spreadsheets are the Swiss army knife of data processing. But there’s another unsung hero of the analytics engineering toolkit: the humble spreadsheet.

Data Warehouse 52

Data Warehouse ETL Tools Google Cloud Cloud Storage 52

Knowledge Hut

FEBRUARY 7, 2023

Once upon a time, Data Science was something that was restricted only to the tech giants, but in this fast-growing world, it is slowly becoming an integral part of businesses as big companies start to integrate these techniques into their business models. It offers all of the tools data scientists need to unlock value from data.

Data Science 52

Data Science Google Cloud Machine Learning Programming Language 52

Edureka

AUGUST 29, 2024

Hence, the systems and architecture need a professional who can keep the data flow from source to destination clean and eliminate any bottlenecks to enable data scientists to pull out insights from the data and transform it into data-driven decisions. What Does a Data Engineer Do?

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Data Engineering Data Engineer Engineering Generalist 40

Knowledge Hut

MARCH 19, 2024

market share, while all of its rivals combined, Microsoft Azure (29.4%), Google Cloud (3.0%), and IBM (2.6%), do not even reach that percentage. That shows how much AWS has to offer, and you must know about it if you’re a cloud computing enthusiast. I will explore the top 10 AWS applications and their use cases in this blog.

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AWS Cloud Computing Amazon Web Services Relational Database 52

Data Science Blog: Data Engineering

NOVEMBER 15, 2023

So whenever you hear that Process Mining can prepare RPA definitions you can expect that Task Mining is the real deal. They enable quicker data processing and decision-making, support advanced analytics and AI with standardized data formats, and are adaptable to changing business needs. Click to enlarge!

Architecture 52

Architecture Database-centric Process BI 52

Knowledge Hut

MARCH 7, 2024

This blog will get you the top ten IoT skills that will be in high demand in 2024, as well as how you may develop them through IoT online courses , projects, and certifications. This makes it ideal for IoT scenarios where real-time data processing and communication are required. Development Node.js

Cloud Computing 52

Cloud Computing Machine Learning Transportation Google Cloud 52

Striim

OCTOBER 11, 2024

As you’ll see by taking a look at this data pipeline example, the complexity and design of a pipeline varies depending on intended use. For instance, Macy’s streams change data from on-premises databases to Google Cloud. Another excellent data pipeline example is American Airlines’ work with Striim.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

AltexSoft

OCTOBER 21, 2022

popular SQL and NoSQL database management systems including Oracle, SQL Server, Postgres, MySQL, MongoDB, Cassandra, and more; cloud storage services — Amazon S3, Azure Blob, and Google Cloud Storage; message brokers such as ActiveMQ, IBM MQ, and RabbitMQ; Big Data processing systems like Hadoop ; and.

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Kafka Hadoop Big Data ETL Tools 93

Knowledge Hut

NOVEMBER 18, 2023

So, if you are thinking of using these solutions in your business, keep reading this blog. Convergence of IoT and Machine Learning The need for analyzing high data volumes and automating these tasks to increase their speed and efficiency has led to the convergence of IoT and machine learning.

Machine Learning 52

Machine Learning Transportation Healthcare Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

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