Unlock the Power of Real-time Data Processing with Databricks and Google Cloud
databricks
JUNE 15, 2023
We are excited to announce the official launch of the Google Pub/Sub connector for the Databricks Lakehouse Platform. This new connector adds to.
Creating a Data Pipeline with Spark, Google Cloud Storage and Big Query
Towards Data Science
MARCH 6, 2023
And that’s the target of today’s post — We’ll be developing a data pipeline using Apache Spark, Google Cloud Storage, and Google Big Query (using the free tier) not sponsored. The tools Spark is an all-purpose distributed memory-based data processing framework geared towards processing extremely large amounts of data.
Google Cloud 
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Agent Tooling: Connecting AI to Your Tools, Systems & Data
How to Modernize Manufacturing Without Losing Control
Mastering Apache Airflow® 3.0: What’s New (and What’s Next) for Data Orchestration
Trending Sources
The Stream Processing Model Behind Google Cloud Dataflow
Towards Data Science
APRIL 30, 2024
Balancing correctness, latency, and cost in unbounded data processing Image created by the author. Intro Google Dataflow is a fully managed data processing service that provides serverless unified stream and batch data processing. Table of contents Before we move on Introduction from the paper.
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Taking A Tour Of The Google Cloud Platform For Data And Analytics
Data Engineering Podcast
JUNE 11, 2021
In this episode Lak Lakshmanan enumerates the variety of services that are available for building your various data processing and analytical systems. He shares some of the common patterns for building pipelines to power business intelligence dashboards, machine learning applications, and data warehouses.
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Top 10 Google Cloud Certifications
Knowledge Hut
AUGUST 18, 2023
With the rise of cloud computing, there’s no better time to explore the top Google Cloud Certifications that can take your career to new heights. Having gone through the process myself, I can attest to the immense value & recognition that comes with earning a Google Cloud Certification.
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Google Cloud Engineer Salary: A Complete Earnings Salary 2023
Knowledge Hut
JULY 31, 2023
Google Cloud has emerged as a leading player in cloud computing and technology solutions. Research suggests that the global cloud computing industry is predicted to develop at a compound annual growth rate (CAGR) of 16.3%, from USD 445.3 Who is a Google Cloud Engineer? Who is a Google Cloud Engineer?
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Google Cloud Pub/Sub: Messaging on The Cloud
ProjectPro
FEBRUARY 6, 2023
With over 10 million active subscriptions, 50 million active topics, and a trillion messages processed per day, Google Cloud Pub/Sub makes it easy to build and manage complex event-driven systems. Google Pub/Sub provides global distribution of messages making it possible to send and receive messages from across the globe.
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Top 9 Trending Google Cloud Career Options to know in 2023
Knowledge Hut
JUNE 30, 2023
Businesses need cloud technologies to host their web applications and run their operations. Google Cloud is one of the leading cloud computing platforms in the world. The best certification to pursue novices is Google Cloud Engineer - Associate. Why Choose a Google Cloud Career?
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Unapologetically Technical Episode 15 – Frances Perry
Jesse Anderson
DECEMBER 25, 2024
Frances Perry is an engineering manager who spent many years as a heads-down coder creating various distributed systems used in Google and Google Cloud.
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Top 10 Data Engineering Trends in 2025
Edureka
APRIL 22, 2025
AI-powered data engineering solutions make it easier to streamline the data management process, which helps businesses find useful insights with little to no manual work. Real-time data processing has emerged The demand for real-time data handling is expected to increase significantly in the coming years.
Connect PostgreSQL on Google Cloud SQL to Amazon Aurora: 2 Ways to Integrate Data
Hevo
SEPTEMBER 26, 2023
As a data-driven business, extracting meaningful data from various sources and making informed decisions relies heavily on effective data analysis. To unlock the full potential of your data in PostgreSQL on Google Cloud SQL necessitates data integration with Amazon Aurora.
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Why Open Table Format Architecture is Essential for Modern Data Systems
phData: Data Engineering
NOVEMBER 8, 2024
This is particularly beneficial in complex analytical queries, where processing smaller, targeted segments of data results in quicker and more efficient query execution. Additionally, the optimized query execution and data pruning features reduce the compute cost associated with querying large datasets.
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Microsoft Fabric vs. Snowflake: Key Differences You Need to Know
Edureka
APRIL 22, 2025
It provides real multi-cloud flexibility in its operations on AWS , Azure, and Google Cloud. Its multi-cluster shared data architecture is one of its primary features. Snowflake: Offers multi-cloud support, which is present on AWS, Azure, and Google Cloud.
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Data Engineering Weekly #177
Data Engineering Weekly
JUNE 24, 2024
[link] Allegro Tech: A Mission to Cost-Effectiveness: Reducing the cost of a single Google Cloud Dataflow Pipeline by Over 60% The blog is an excellent case study of hyopoesis driven cost optimization with the detail analysis to verify the hypothesis. Physical resources are underutilized. Are there enough usecases?
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How To Future-Proof Your Data Pipelines
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. Set Up Auto-Scaling: Configure auto-scaling for your data processing and storage resources.
Is Data Engineering a must for Data Scientists?
Team Data Science
DECEMBER 17, 2020
It’s not a must for data scientist to have skill in data engineering before they can analyze data processed by data engineer or before they can move uniformly with other group (involving data engineer) for the progress of the company. Data scientists should acquire some basic SQL functionality.
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Integrating Striim with BigQuery ML: Real-time Data Processing for Machine Learning
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.
The Future of Business Intelligence is Open Source
Maxime Beauchemin
MARCH 8, 2021
For those reasons, it is not surprising that it has taken over most of the modern data stack: infrastructure, databases, orchestration, data processing, AI/ML and beyond. This isn’t a new phenomenon.
The Race For Data Quality in a Medallion Architecture
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.
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What is an AI Data Engineer? 4 Important Skills, Responsibilities, & Tools
Monte Carlo
OCTOBER 31, 2024
Big Data and Cloud Infrastructure Knowledge Lastly, AI data engineers should be comfortable working with distributed data processing frameworks like Apache Spark and Hadoop, as well as cloud platforms like AWS, Azure, and Google Cloud.
On-Prem vs. The Cloud: Key Considerations
phData: Data Engineering
FEBRUARY 21, 2025
The Cloud represents an iteration beyond the on-prem data warehouse, where computing resources are delivered over the Internet and are managed by a third-party provider. Examples include: Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP).
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Geospatial Index 102
Towards Data Science
APRIL 11, 2023
(Note: If you have never heard of the geospatial index or would like to learn more about it, check out this article ) Data The data used in this article is the Chicago Crime Data which is a part of the Google Cloud Public Dataset Program. Anyone with a Google Cloud Platform account can access this dataset for free.
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Stream Processing with Python, Kafka & Faust
Towards Data Science
FEBRUARY 18, 2024
Lastly, I share my experience implementing a similar pipeline on the Google Cloud Platform. Stream Processing A stream refers to unbounded data that is incrementally made available over time. Google Cloud Solution I would like to briefly discuss my negative experience with the Google Cloud Platform (GCP).
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The Intersection of GenAI and Streaming Data: What’s Next for Enterprise AI?
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.
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Leading The Charge For The ELT Data Integration Pattern For Cloud Data Warehouses At Matillion
Data Engineering Podcast
MAY 1, 2022
The ecosystems of both cloud technologies and data processing have been rapidly growing and evolving, with new patterns and paradigms being introduced. The ecosystems of both cloud technologies and data processing have been rapidly growing and evolving, with new patterns and paradigms being introduced.
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Data Engineering Weekly #173
Data Engineering Weekly
MAY 26, 2024
[link] Sponsored: 5/30 Google BigQuery Data Integration Tech Talk Scale data pipelines to and from BigQuery for GenAI, Business Intelligence, and Operations. Is massive scale data warehouses like Snowflake or data processing engines like Spark require for incremental processing?
A Definitive Guide to Using BigQuery Efficiently
Towards Data Science
MARCH 5, 2024
In that case, queries are still processed using the BigQuery compute infrastructure but read data from GCS instead. Such external tables come with some disadvantages but in some cases it can be more cost efficient to have the data stored in GCS. Data can easily be uploaded and stored for low costs.
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Machine Learning with Python, Jupyter, KSQL and TensorFlow
Confluent
FEBRUARY 6, 2019
Managed model server in the public cloud like Google Cloud Machine Learning Engine: The cloud provider takes over the burden of availability and reliability. The data scientist “just” deploys its trained model, and production engineers can access it. Apache Kafka and KSQL for data scientists and data engineers.
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How Leaders of the Modern Marketing Data Stack Differentiate Themselves in a Crowded Market
Snowflake
SEPTEMBER 21, 2023
The Snowflake Native App Framework on Google Cloud and Azure is currently in private preview.) At Snowflake Summit in June 2023, Snowflake launched Snowflake Native Apps in public preview on AWS to address these vendor and brand challenges.
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Data Engineering Weekly #170
Data Engineering Weekly
MAY 5, 2024
Platform PayPal writes about its internal AI platform cosmos.ai, which provides MLOps capabilities that streamline processes like model training, deployment, and monitoring, significantly reducing complexity and costs.
Parcel Protection: Inside UPS Capital’s Defensive Strategy with Striim & Google
Striim
MAY 1, 2024
The sheer volume of data generated from the increasing package deliveries overwhelmed existing data management systems, underscoring a critical need for more advanced data handling capabilities. The absence of real-time data processing capabilities hindered UPS Capital’s risk management and rapid response efforts.
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What is Google Dataflow?
Hevo
FEBRUARY 7, 2025
Have you heard of the Google Cloud Platform, offering a completely managed stream and batch data processing service? Well, this modern data engineering technology plays an essential part in dealing efficiently and quickly with massive amounts of data.
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GCP Oracle Migration: Optimize your Workload
Hevo
JUNE 19, 2024
Oracle is widely used to store, manage, and perform complex operations on data, making it ideal for business-critical operations. You can efficiently scale your business data by hosting Oracle services on the Google Cloud Platform. Integrating these […]
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Top-10 Open Source Data Orchestration Tools
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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Top 10 Real World Applications of Cloud Computing
Knowledge Hut
NOVEMBER 7, 2023
Google Cloud Google Cloud is a dependable, user-friendly, and secure cloud computing solution from one of today's most powerful technology companies. Despite having a smaller service portfolio than Azure, Google Cloud can nonetheless fulfill all of your IaaS and PaaS needs.
Apache Airflow and the Future of Data Engineering: A Q&A
Maxime Beauchemin
FEBRUARY 28, 2017
Highcharts has a non-Apache compatible license and ripping it out takes us out of a legal grey zone Unix impersonation and cgroups, allowing to run tasks as a specific Unix user, and specifying cgroups to limit resource usage at the task level.
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Serverless NiFi Flows with DataFlow Functions: The Next Step in the DataFlow Service Evolution
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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15+ Best Data Engineering Tools to Explore in 2023
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?
Top 12 Data Engineering Project Ideas [With Source Code]
Knowledge Hut
JUNE 26, 2023
If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source Code: Finnhub API with Kafka for Real-Time Financial Market Data Pipeline 3.
Internet of Things (IoT) and Event Streaming at Scale with Apache Kafka and MQTT
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.
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AWS vs GCP - Which One to Choose in 2023?
ProjectPro
SEPTEMBER 6, 2021
So, are you ready to explore the differences between two cloud giants, AWS vs. google cloud? Amazon brought innovation in technology and enjoyed a massive head start compared to Google Cloud, Microsoft Azure , and other cloud computing services. GCP Storage Google Cloud storage provides high availability.
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8 Data Ingestion Tools (Quick Reference Guide)
Monte Carlo
FEBRUARY 20, 2024
Let’s explore what to consider when thinking about data ingestion tools and explore the leading tools in the field. Consideration What to Look For Integration Capabilities Support for a diverse array of data sources and destinations, ensuring compatibility with your data ecosystem.
What is Machine Learning Engineer: Responsibilities, Skills, and Value Brought
AltexSoft
JUNE 29, 2021
Machine Learning and Artificial Intelligence on Google Cloud. The certificate offered by Google covers both data scientist and machine learning engineer skills. It introduces Google’s ML, AI, and Big Data products — namely, BigQuery, Cloud SQL, and AI platform. IBM Advanced Data Science.
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Top Web Development Trends to Watch Out for in 2024
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.
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