Smart Data Collective

APRIL 24, 2023

Google’s Hadoop allowed for unlimited data storage on inexpensive servers, which we now call the Cloud. In this blog post, we will discuss the five best server backup software solutions that businesses can consider in 2023. Searching for a topic on a search engine can provide us with a vast amount of information in seconds.

Big Data 119

Big Data Big Data Hadoop Azure 119

phData

MARCH 7, 2023

Prerequisites In this blog, we focus on ingesting data into the Snowflake Data Cloud with GoldenGate and so we will pick up the replication process within GoldenGate. gg.eventhandler.hdfs.finalizeAction=delete #TODO: Edit snowflake storage integration to access Azure Blob Storage. share/hadoop/common/*:hadoop-3.2.1/share/hadoop/common/lib/*:hadoop-3.2.1/share/hadoop/hdfs/*:hadoop-3.2.1/share/hadoop/hdfs/lib/*:hadoop-3.2.1/etc/hadoop/:hadoop-3.2.1/share/hadoop/tools/li

Hadoop 59

Hadoop Database Data Warehouse AWS 59

Data Science Dojo

JULY 3, 2024

In this blog, we will explore the arena of data science bootcamps and lay down a guide for you to choose the best data science bootcamp. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. What do Data Science Bootcamps Offer?

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

DataRobot Blog

OCTOBER 3, 2017

Many announcements at Strata centered on product integrations, with vendors closing the loop and turning tools into solutions, most notably: A Paxata-HDInsight solution demo, where Paxata showcased the general availability of its Adaptive Information Platform for Microsoft Azure. Alation and Paxata announced their product integration.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

Pickl AI

JULY 25, 2023

With expertise in programming languages like Python , Java , SQL, and knowledge of big data technologies like Hadoop and Spark, data engineers optimize pipelines for data scientists and analysts to access valuable insights efficiently. Big Data Technologies: Hadoop, Spark, etc. Big Data Processing: Apache Hadoop, Apache Spark, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

JUNE 7, 2024

This blog will delve into ETL Tools, exploring the top contenders and their roles in modern data integration. Key Features Out-of-the-Box Connectors: Includes connectors for databases like Hadoop, CRM systems, XML, JSON, and more. Cost Considerations: Implementing and maintaining Hadoop clusters can incur significant costs.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

DagsHub

DECEMBER 11, 2023

To help data practitioners, this blog will cover eight of the top data versioning tools in the market. Best data version control tools for 2024 Now that you have a clear understanding of the expectations of the blog, let’s explore each one of them, starting with DagsHub. Why do we need to version our data?

Machine Learning 98

Machine Learning Machine Learning Data Lakes Data Science 98

IBM Journey to AI blog

JANUARY 18, 2023

This is an architecture that’s well suited for the cloud since AWS S3 or Azure DLS2 can provide the requisite storage. It can include technologies that range from Oracle, Teradata and Apache Hadoop to Snowflake on Azure, RedShift on AWS or MS SQL in the on-premises data center, to name just a few. Yet, the overlap is evident.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

NOVEMBER 28, 2024

Summary: The blog discusses essential skills for Machine Learning Engineer, emphasising the importance of programming, mathematics, and algorithm knowledge. This blog outlines essential Machine Learning Engineer skills to help you thrive in this fast-evolving field. The global Machine Learning market was valued at USD 35.80

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

MARCH 11, 2025

In this blog, we will break down these two concepts, highlight their key differences, and help you understand how they work. Cloud platforms like AWS and Azure support Big Data tools, reducing costs and improving scalability. Companies like Amazon Web Services (AWS) and Microsoft Azure provide this service.

Cloud Computing 52

Cloud Computing Big Data Big Data Big Data Analytics 52

Pickl AI

APRIL 2, 2024

Summary This blog post demystifies data science for business leaders. This blog post serves as a cheat sheet for business leaders, providing a high-level understanding of data science, its applications, and how to leverage it for success. Hadoop/Spark: Frameworks for distributed storage and processing of big data.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Pickl AI

DECEMBER 4, 2024

This blog explores the current state of Data Science, emerging trends, the role of generative AI, decision-making enhancements, ethical challenges, essential skills for future Data Scientists, and predictions for the next decade. AWS or Azure) will be increasingly important as more organisations migrate their operations online.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Heartbeat

JULY 31, 2023

Comet also integrates with popular data storage and processing tools like Amazon S3, Google Cloud Storage, and Hadoop. Comet also works with popular cloud platforms like AWS, GCP, and Azure, making it easy to deploy models to the cloud with just a few clicks. We pay our contributors, and we don’t sell ads.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

The MLOps Blog

JANUARY 23, 2023

It supports most major cloud providers, such as AWS, GCP, and Azure. LakeFS is fully compatible with many ecosystems of data engineering tools such as AWS, Azure, Spark, Databrick, MlFlow, Hadoop and others. The remote repository can be on the same computer, or it can be on the cloud.

ML 52

ML ML Data Lakes Machine Learning 52

The MLOps Blog

MAY 31, 2023

To store Image data, Cloud storage like Amazon S3 and GCP buckets, Azure Blob Storage are some of the best options, whereas one might want to utilize Hadoop + Hive or BigQuery to store clickstream and other forms of text and tabular data. One might want to utilize an off-the-shelf ML Ops Platform to maintain different versions of data.

ML 59

ML ML Algorithm Machine Learning 59

Data Science Blog

MAY 15, 2023

Data Lakehouses werden auf Cloud-basierten Objektspeichern wie Amazon S3 , Google Cloud Storage oder Azure Blob Storage aufgebaut. Spark ist direkt auf mehreren Cloud-Plattformen verfügbar, darunter AWS, Azure und Google Cloud Platform.Apacke Spark ist jedoch mehr als nur ein Tool, es ist die Grundbasis für die meisten anderen Tools.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

How to Learn Machine Learning

MAY 3, 2025

All the clouds are different, and for us GCP offers some cool benefits that we will highlight in this article vs the AWS AI Services or Azure Machine Learning. Dataproc Process large datasets with Spark and Hadoop before feeding them into your ML pipeline. This blog post was last updated on May 2, 2025. Ready to start building?

Machine Learning 59

Machine Learning Machine Learning AI AI 59

Pickl AI

MARCH 19, 2025

In this blog, well explore the best data engineering tools that make data work easier, faster, and more reliable. Apache Hive Apache Hive is a data warehouse tool that allows users to query and analyse large datasets stored in Hadoop. Microsoft Azure Synapse Analytics : A cloud-based analytics service for Big Data and Machine Learning.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52