Analytics Vidhya

MARCH 8, 2023

The Biggest Data Science Blogathon is now live! Knowledge is power. Sharing knowledge is the key to unlocking that power.”― Martin Uzochukwu Ugwu Analytics Vidhya is back with the largest data-sharing knowledge competition- The Data Science Blogathon.

Data Science 345

Data Science Analytics Analytics Apache Hadoop 345

Analytics Vidhya

JANUARY 8, 2023

Hey, are you the data science geek who spends hours coding, learning a new language, or just exploring new avenues of data science? If all of these describe you, then this Blogathon announcement is for you! Analytics Vidhya is back with its 28th Edition of blogathon, a place where you can share your knowledge about […].

Data Science 328

Data Science Analytics Analytics Hadoop 328

phData

NOVEMBER 8, 2024

Cost Efficiency and Scalability Open Table Formats are designed to work with cloud storage solutions like Amazon S3, Google Cloud Storage, and Azure Blob Storage, enabling cost-effective and scalable storage solutions. Amazon S3, Azure Data Lake, or Google Cloud Storage).

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

Analytics Vidhya

NOVEMBER 7, 2022

Hello, fellow data science enthusiasts, did you miss imparting your knowledge in the previous blogathon due to a time crunch? Well, it’s okay because we are back with another blogathon where you can share your wisdom on numerous data science topics and connect with the community of fellow enthusiasts.

Data Science 306

Data Science Analytics Analytics Hadoop 306

phData

MARCH 7, 2023

#The S3 Event Handler #TODO: Edit the AWS region #gg.eventhandler.s3.region= region= #TODO: Edit the AWS S3 bucket #gg.eventhandler.s3.bucketMappingTemplate= bucketMappingTemplate= #TODO:Set the classpath to include AWS Java SDK and Snowflake JDBC driver. jar #TODO:Set the AWS access key and secret key. gg.classpath=./snowflake-jdbc-3.13.7.jar:hadoop-3.2.1/share/hadoop/common/*:hadoop-3.2.1/share/hadoop/common/lib/*:hadoop-3.2.1/share/hadoop/hdfs/*:hadoop-3.2.1/share/

Hadoop 59

Hadoop Database Data Warehouse AWS 59

Smart Data Collective

APRIL 24, 2023

Google’s Hadoop allowed for unlimited data storage on inexpensive servers, which we now call the Cloud. Searching for a topic on a search engine can provide us with a vast amount of information in seconds. Deighton studies how this evolution came to be. Innovations in the early 20th century changed how data could be used.

Big Data 119

Big Data Big Data Hadoop Azure 119

Pickl AI

DECEMBER 25, 2024

Big data platforms such as Apache Hadoop and Spark help handle massive datasets efficiently. They must also stay updated on tools such as TensorFlow, Hadoop, and cloud-based platforms like AWS or Azure. Machine learning algorithms play a central role in building predictive models and enabling systems to learn from data.

Data Science 52

Data Science Analytics Analytics Data Scientist 52

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Cloud Computing : Utilizing cloud services for data storage and processing, often covering platforms such as AWS, Azure, and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Precisely

MARCH 9, 2023

Hadoop, Snowflake, Databricks and other products have rapidly gained adoption. We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

ODSC - Open Data Science

JUNE 7, 2023

Microsoft’s Azure Data Lake The Azure Data Lake is considered to be a top-tier service in the data storage market. Amazon Web Services Similar to Azure, Amazon Simple Storage Service is an object storage service offering scalability, data availability, security, and performance.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

Pickl AI

JUNE 7, 2024

Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Key Features Out-of-the-Box Connectors: Includes connectors for databases like Hadoop, CRM systems, XML, JSON, and more.

ETL 40

ETL Data Quality Data Pipeline Data Warehouse 40

Pickl AI

NOVEMBER 4, 2024

Among these tools, Apache Hadoop, Apache Spark, and Apache Kafka stand out for their unique capabilities and widespread usage. Apache Hadoop Hadoop is a powerful framework that enables distributed storage and processing of large data sets across clusters of computers.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Pickl AI

JANUARY 13, 2025

Key Skills Experience with cloud platforms (AWS, Azure). Hadoop , Apache Spark ) is beneficial for handling large datasets effectively. Cloud Computing Skills Familiarize yourself with cloud platforms like AWS , Google Cloud , or Microsoft Azure to manage infrastructure and deploy AI models efficiently.

AI 52

AI AI Machine Learning Machine Learning 52

Mlearning.ai

MAY 23, 2023

Check out this course to build your skillset in Seaborn —  [link] Big Data Technologies Familiarity with big data technologies like Apache Hadoop, Apache Spark, or distributed computing frameworks is becoming increasingly important as the volume and complexity of data continue to grow.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 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 Engineer Data Engineering Data Engineering 52

Mlearning.ai

JANUARY 28, 2023

Spark: Spark is a popular platform used for big data processing in the Hadoop ecosystem. Using a cloud provider such as Google Cloud Platform, Amazon AWS, Azure Cloud, or IBM SoftLayer 2. Deploying a machine learning library in the cloud can be difficult.

Machine Learning 52

Machine Learning Machine Learning Data Science ML 52

Mlearning.ai

MARCH 15, 2023

Experience with cloud platforms like; AWS, AZURE, etc. Knowledge of big data platforms like; Hadoop and Apache Spark. Experience with machine learning frameworks for supervised and unsupervised learning. Experience with visualization tools like; Tableau and Power BI.

Data Science 52

Data Science Analytics Analytics Data Analyst 52

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.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

MARCH 11, 2025

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. It supports Big Data tools like Hadoop and Spark, allowing businesses to scale analytics operations efficiently.

Cloud Computing 52

Cloud Computing Big Data Big Data Big Data Analytics 52

Pickl AI

NOVEMBER 28, 2024

Cloud platforms like AWS , Google Cloud Platform (GCP), and Microsoft Azure provide managed services for Machine Learning, offering tools for model training, storage, and inference at scale. Big Data Tools Integration Big data tools like Apache Spark and Hadoop are vital for managing and processing massive datasets.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

DagsHub

OCTOBER 23, 2024

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. Apache Hadoop Apache Hadoop is an open-source framework that supports the distributed processing of large datasets across clusters of computers. Data Processing Tools These tools are essential for handling large volumes of unstructured data.

Machine Learning 52

Machine Learning Machine Learning AI AI 52

The MLOps Blog

JANUARY 23, 2023

It supports most major cloud providers, such as AWS, GCP, and Azure. datasets/images" ) In order to store artifacts from Amazon S3, we need to configure an IAM policy with “S3ReadAccessOnly” permissions and store our credentials for AWS as environment variables. size: Size of the file, in kilobytes.

ML 52

ML ML Data Lakes Machine Learning 52

ODSC - Open Data Science

JANUARY 7, 2025

From development environments like Jupyter Notebooks to robust cloud-hosted solutions such as AWS SageMaker, proficiency in these systems is critical. Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

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.

Machine Learning 52

Machine Learning Machine Learning Deep Learning Deep Learning 52

DagsHub

NOVEMBER 11, 2024

Platforms like Azure Data Lake and AWS Lake Formation can facilitate big data and AI processing. Distributed File Systems Distributed file systems (DFSs), like Hadoop HDFS , are essential for storing and managing large amounts of unstructured data that AI systems need for analysis and training models.

AI 52

AI AI Data Lakes Database 52

Data Science Dojo

MAY 24, 2024

Java is also widely used in big data technologies, supported by powerful Java-based tools like Apache Hadoop and Spark, which are essential for data processing in AI. Big Data Technologies With the growth of data-driven technologies, AI engineers must be proficient in big data platforms like Hadoop, Spark, and NoSQL databases.

AI 195

AI AI Deep Learning Deep Learning 195

Pickl AI

DECEMBER 4, 2024

Gain Experience with Big Data Technologies With the rise of Big Data, familiarity with technologies like Hadoop and Spark is essential. Familiarise yourself with cloud platforms like AWS, Google Cloud Platform , or Microsoft Azure for storing and processing large datasets. Additionally, familiarity with cloud platforms (e.g.,

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

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

APRIL 2, 2024

Hadoop/Spark: Frameworks for distributed storage and processing of big data. Cloud Platforms (AWS, Azure, Google Cloud): Infrastructure for scalable and cost-effective data storage and analysis. SQL (Structured Query Language): Language for managing and querying relational databases.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Key Features : Scalability : Hadoop can handle petabytes of data by adding more nodes to the cluster. Use Cases : Yahoo!

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

Pickl AI

MARCH 19, 2025

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. Hadoop : An open-source framework for processing Big Data across multiple servers.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52