ODSC - Open Data Science

MAY 31, 2023

Commonly used technologies for data storage are the Hadoop Distributed File System (HDFS), Amazon S3, Google Cloud Storage (GCS), or Azure Blob Storage, as well as tools like Apache Hive, Apache Spark, and TensorFlow for data processing and analytics. Subscribe to our weekly newsletter here and receive the latest news every Thursday.

Data Lakes 131

Data Lakes Machine Learning Machine Learning Apache Kafka 131

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. So, what are you waiting for?

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

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 Engineering Data Engineering Data Engineer 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. Artificial Intelligence : Concepts of AI include neural networks, natural language processing (NLP), and reinforcement learning.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

NOVEMBER 5, 2024

Its popularity stems from its user-friendly interface and seamless integration with widely used Microsoft applications like Excel and Azure, making it highly accessible for organisations already using Microsoft products. Tableau+: An AI-powered analytics package is available on Tableau Cloud.

Power BI 52

Power BI Tableau Business Intelligence Business Intelligence 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

DagsHub

OCTOBER 23, 2024

This article will discuss managing unstructured data for AI and ML projects. You will learn the following: Why unstructured data management is necessary for AI and ML projects. How to leverage Generative AI to manage unstructured data Benefits of applying proper unstructured data management processes to your AI/ML project.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

JUNE 7, 2024

Wide Range of Data Services: Integrates well with various data services, including data warehousing and AI applications. 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

Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Cloud Storage: Services like Amazon S3, Google Cloud Storage, and Microsoft Azure Blob Storage provide scalable storage solutions that can accommodate massive datasets with ease. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Cloud Storage: Services like Amazon S3, Google Cloud Storage, and Microsoft Azure Blob Storage provide scalable storage solutions that can accommodate massive datasets with ease. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

DagsHub

NOVEMBER 11, 2024

In this article, we’ll explore how AI can transform unstructured data into actionable intelligence, empowering you to make informed decisions, enhance customer experiences, and stay ahead of the competition. Let’s look at how we can convert unstructured data into better informative structures using new AI techniques and solutions.

AI 52

AI AI Data Lakes Database 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

IBM Journey to AI blog

JANUARY 18, 2023

Furthermore, data warehouse storage cannot support workloads like Artificial Intelligence (AI) or Machine Learning (ML), which require huge amounts of data for model training. This is an architecture that’s well suited for the cloud since AWS S3 or Azure DLS2 can provide the requisite storage. appeared first on Journey to AI Blog.

Data Lakes 52

Data Lakes Data Warehouse Apache Hadoop Azure 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

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

DECEMBER 11, 2023

LakeFS Most big data storage solutions such as Azure, Google cloud storage, and Amazon S3 have good performance, cost-effective, and have good connectivity with other tooling. Such a server is not provided by every Git hosting service and in some cases will require either setting it up or switching to a different Git provider.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Big Data 98

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. Google App Engine is an example.

Cloud Computing 52

Cloud Computing Big Data Big Data Big Data Analytics 52

ODSC - Open Data Science

JANUARY 7, 2025

Deep Learning Deep learning is a cornerstone of modern AI, and its applications are expanding rapidly. Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments. Kafka remains the go-to for real-time analytics and streaming.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

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 Dojo

MAY 24, 2024

From healthcare where AI assists in diagnosis and treatment plans, to finance where it is used to predict market trends and manage risks, the influence of AI is pervasive and growing. As AI technologies evolve, they create new job roles and demand new skills, particularly in the field of AI engineering.

Machine Learning 195

Machine Learning Machine Learning Deep Learning Deep Learning 195

Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. Key Takeaways AI and Machine Learning will advance significantly, enhancing predictive capabilities across industries. Here are five key trends to watch.

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

Machine Learning: Subset of AI that enables systems to learn from data without being explicitly programmed. 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.

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. Databricks : A cloud-based platform that simplifies Big Data and AI workloads. 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