Striim

JUNE 4, 2024

Contrary to traditional methods, such as batch processing where data is collected, stored, and analyzed at a later time, with real-time processing there’s no delay even for high-velocity data sets. This data must be ingested with minimal latency to ensure it is available for immediate processing.

Machine Learning 52

Machine Learning Algorithm Healthcare Utilities 52

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

Knowledge Hut

MARCH 19, 2024

AWS is the gold standard of Cloud Computing and has some reasons for it. 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.

AWS 52

AWS Cloud Computing Amazon Web Services Relational Database 52

Monte Carlo

APRIL 24, 2023

With our new partnership and updated integration, Monte Carlo provides full, end-to-end coverage across data lake and lakehouse environments powered by Databricks. But remember that line from the introduction about the blurring line between data warehouses and data lakes? It works in both directions.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

ProjectPro

FEBRUARY 21, 2023

Vendor-Specific Data Engineering Certifications The vendor-specific data engineer certifications help you enhance your knowledge and skills relevant to specific vendors, such as Azure, Google Cloud Platform, AWS, and other cloud service vendors. Expertise in leveraging cloud platforms, data services, and solutions.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

FEBRUARY 20, 2024

At the heart of every data-driven decision is a deceptively simple question: How do you get the right data to the right place at the right time? The growing field of data ingestion tools offers a range of answers, each with implications to ponder. Fivetran Image courtesy of Fivetran.

Data Ingestion 52

Data Ingestion Google Cloud Kafka AWS 52

Data Engineering Podcast

NOVEMBER 14, 2017

To surface the insights that they need to grow their business they need a robust data infrastructure to reliably capture all of those interactions. Preamble Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to launch your next project you’ll need somewhere to deploy it.

Google Cloud 100

Google Cloud Data Ingestion Media AWS 100

Snowflake

AUGUST 16, 2023

The Snowflake Native App Framework remains available in private preview on Google Cloud Platform and Azure. That’s why we built Snowpipe Streaming, now generally available to handle row-set data ingestion. See Snowflake documentation on how to set up Cross-Cloud Auto-Fulfillment on your listings. Learn more here.

Scala 52

Scala Transportation Kafka Data Lake 52

Knowledge Hut

JUNE 26, 2023

Hundreds of datasets are available from these two cloud services, so you may practise your analytical skills without having to scrape data from an API. Source: Use Stack Overflow Data for Analytic Purposes 4. A dashboard that provides data in a graphical manner for in-depth study is the final product of this project.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

dbt Developer Hub

JANUARY 14, 2023

The builder: I’m a data freelancer who deploys end to end solutions, so when I have a data problem, I cannot just let it go. The tools: I want to be able to run my project on Google Cloud Functions due to the generous free tier. Transforming the data ​ For transforming I use my favorite solution, dbt Core.

Data Ingestion 52

Data Ingestion Google Cloud Python Cloud 52

Knowledge Hut

MARCH 28, 2024

Azure Data Engineer Career Demands & Benefits Azure has become one of the most powerful platforms in the industry, where Microsoft offers a variety of data services and analytics tools. As a result, organizations are looking to capitalize on cloud-based data solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Cloudera

MARCH 31, 2021

CDP Public Cloud is now available on Google Cloud. The addition of support for Google Cloud enables Cloudera to deliver on its promise to offer its enterprise data platform at a global scale. CDP Public Cloud is already available on Amazon Web Services and Microsoft Azure.

Google Cloud 94

Google Cloud Cloud Amazon Web Services Cloud Storage 94

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers.

Machine Learning 106

Machine Learning Python Kafka Java 106

ProjectPro

JANUARY 19, 2022

Independently create data-driven solutions that are accurate and informative. Interact with the data scientists team and assist them in providing suitable datasets for analysis. Leverage various big data engineering tools and cloud service providing platforms to create data extractions and storage pipelines.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Rockset

MARCH 21, 2019

When we started Rockset, we envisioned building a powerful cloud data management system that was really easy to use. Making the data stack simpler is fundamental to making data usable by developers and data scientists. Another key aspect of Rockset that makes it simple to use is its serverless nature.

SQL 52

SQL Data Management Management Engineering 52

Rockset

JULY 29, 2022

Google BigQuery BigQuery is Google’s data warehouse service and one of the first cloud data warehouses released to the public. However, the data via its streaming API insert isn’t available for two to three minutes. So, it’s not real-time data. The Snowpipe feature manages continuous data ingestion.

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

Data Engineering Podcast

NOVEMBER 20, 2022

report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. The Ascend Data Automation Cloud provides a unified platform for data ingestion, transformation, orchestration, and observability. Support Data Engineering Podcast In fact, while only 3.5%

Data Lake 130

Data Lake Data Ingestion MongoDB Scala 130

Cloudera

DECEMBER 15, 2022

For example, Modak Nabu is helping their enterprise customers accelerate data ingestion, curation, and consumption at petabyte scale. Today, we are thrilled to share some new advancements in Cloudera’s integration of Apache Iceberg in CDP to help accelerate your multi-cloud open data lakehouse implementation.

Cloud 79

Cloud Metadata Google Cloud Data Warehouse 79

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. In Snowflake, there are three different storage layers available, Database, Stage, and Cloud Storage.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

Ascend.io

DECEMBER 21, 2022

21, 2022 – Ascend.io , The Data Automation Cloud, today announced they have partnered with Snowflake , the Data Cloud company, to launch Free Ingest , a new feature that will reduce an enterprise’s data ingest cost and deliver data products up to 7x faster by ingesting data from all sources into the Snowflake Data Cloud quickly and easily.

Data Ingestion 52

Data Ingestion Google Cloud Data Lake Cloud 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. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

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. Load data For data ingestion Google Cloud Storage is a pragmatic way to solve the task.

Bytes 67

Bytes Google Cloud Cloud Storage Utilities 67

ProjectPro

AUGUST 24, 2021

Data Engineering Project for Beginners If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of data engineering project examples below. This big data project discusses IoT architecture with a sample use case.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Monte Carlo

JUNE 14, 2023

Why is data pipeline architecture important? Data pipeline architecture typically consisted of hardcoded pipelines that cleaned, normalized, and transformed the data prior to loading into a database using an ETL pattern. Data could now be extracted and loaded prior to being transformed for its ultimate use.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Striim

APRIL 1, 2024

Striim Cloud for Application Integration provides a crucial solution to this issue, designed to improve the connectivity and usefulness of these applications by enabling their smooth integration into Google Cloud’s BigQuery. What is Striim Cloud for Application Integration?

Hospitality 52

Hospitality Transportation Google Cloud Cloud 52

Rockset

JANUARY 9, 2023

Modern Snack-Sized Sales Training At ConveYour , we provide automated sales training via the cloud. Technical Challenges Our original data infrastructure was built around an on-premises MongoDB database that ingested and stored all user transaction data. First is its speed at data ingestion.

MySQL 52

MySQL MongoDB Recruitment Data Ingestion 52

AltexSoft

JULY 29, 2022

To facilitate data ingestion, there are Apache Flume aggregating log data from multiple servers and Apache Sqoop designed to transport information between Hadoop and relational (SQL) databases. Today, companies have the opportunity to run Big Data analytics on Hadoop without investing in hardware.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Confluent

MAY 22, 2019

Most IoT-based applications (both B2C and B2B) are typically built in the cloud as microservices and have similar characteristics. It is helpful to think about the data created by the devices and the applications in three stages: Stage one is the initial creation, which takes place on the device, and is then sent over the network.

Kafka 96

Kafka Google Cloud NoSQL Entertainment 96

Knowledge Hut

JULY 6, 2023

IT Professionals looking to work in the cloud domain are expected to have a sound understanding of Azure tools as well as development and monitoring tools. Azure Monitoring Tools: Overview Microsoft Azure is the second-most popular cloud service provider, next to Amazon Web Service. Why are Azure Tools Important?

Amazon Web Services 52

Amazon Web Services Data Lake Java SQL 52

AltexSoft

SEPTEMBER 21, 2023

Accessible via a unified API, these new features enhance search relevance and are available on Elastic Cloud. The Elastic Stacks Elasticsearch is integral within analytics stacks, collaborating seamlessly with other tools developed by Elastic to manage the entire data workflow — from ingestion to visualization.

Engineering 52

Engineering NoSQL Programming Language Java 52

ProjectPro

NOVEMBER 15, 2021

As per the surveyors, Big data (35 percent), Cloud computing (39 percent), operating systems (33 percent), and the Internet of Things (31 percent) are all expected to be impacted by open source shortly. Following these statistics, big data is set to get bigger with the evolution of open-source projects.

Big Data 52

Big Data Project Metadata Programming Language 52

Confluent

OCTOBER 10, 2019

Before I discuss these in more detail, let’s take a look at some common use cases where Confluent Platform and Confluent Cloud are used for IoT projects today. Confluent Platform and Confluent Cloud are already used in many IoT deployments, both in Consumer IoT and Industrial IoT (IIoT). Hybrid, multi-cloud, and global deployments.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20

ProjectPro

OCTOBER 20, 2021

The orchestration of pipelines can happen on various platforms but are generally integrated with cloud providers such as Microsoft Azure, Amazon Web Services , or Google Cloud Platform at an Enterprise Level. AI Interview Questions and Answers on AI Cloud Services 6) What is an API? 8) What Cloud Service would you prefer?

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

phData: Data Engineering

JANUARY 3, 2022

You may need to build another data center or work with a cloud provider to have another set of infrastructure to failover to. Many companies go with cloud providers to ensure availability, reduce infrastructure management, and reduce their security footprint. This could be on-premises servers or cloud providers.

IT 52

IT AWS Software Engineer Software Engineering 52

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Confluent

OCTOBER 16, 2019

Rapid analysis and visualisation of the real-time feed—in addition to historical data—is provided through Elasticsearch and Kibana. For more advanced analytics work, the data is written to two places: a traditional RDBMS (PostgreSQL) and a cloud object store (Amazon S3). SELECT * FROM TRAIN_CANCELLATIONS_00 ; Data sinks.

Kafka 19

Kafka Building Data Coding 19

Confluent

JULY 3, 2019

Twitter represents the default source for most event streaming examples, and it’s particularly useful in our case because it contains high-volume event streaming data with easily identifiable keywords that can be used to filter for relevant topics. Ingesting Twitter data. Sentiment; import com.google.cloud.language.v1.AnalyzeSentimentResponse;

Data Analysis 21

Data Analysis Kafka Datasets Java 21