Analytics Vidhya

JUNE 27, 2020

Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20. The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya.

Data Science 400

Data Science Machine Learning Machine Learning Analytics 400

Data Science Dojo

JULY 24, 2023

Spark provides a high-level API in multiple languages like Scala, Python, Java, and SQL, making it accessible to a wide range of developers. Spark offers a more flexible and memory-resilient approach, allowing for iterative data processing and in-memory caching, which significantly improves performance.

Big Data 195

Big Data Big Data Data Engineering Data Engineering 195

AWS Machine Learning Blog

APRIL 19, 2023

Streaming ingestion – An Amazon Kinesis Data Analytics for Apache Flink application backed by Apache Kafka topics in Amazon Managed Streaming for Apache Kafka (MSK) (Amazon MSK) calculates aggregated features from a transaction stream, and an AWS Lambda function updates the online feature store.

ML 92

ML ML Apache Kafka SQL 92

IBM Journey to AI blog

AUGUST 29, 2024

The unique advantages of Apache Flink Apache Flink augments event streaming technologies like Apache Kafka to enable businesses to respond to events more effectively in real time. Integration: Integrates seamlessly with other data systems and platforms, including Apache Kafka, Spark, Hadoop and various databases.

Apache Kafka 45

Apache Kafka Hadoop ETL Data Pipeline 45

IBM Journey to AI blog

NOVEMBER 29, 2023

IBM Event Automation is a fully composable solution, built on open technologies, with capabilities for: Event streaming : Collect and distribute raw streams of real-time business events with enterprise-grade Apache Kafka. Event endpoint management : Describe and document events easily according to the Async API specification.

Artificial Intelligence 105

Artificial Intelligence Artificial Intelligence Apache Kafka Machine Learning 105

AWS Machine Learning Blog

OCTOBER 9, 2024

Using Amazon Redshift ML for anomaly detection Amazon Redshift ML makes it easy to create, train, and apply machine learning models using familiar SQL commands in Amazon Redshift data warehouses. To start using CloudWatch anomaly detection, you first must ingest data into CloudWatch and then enable anomaly detection on the log group.

AWS 87

AWS ML ML Data Quality 87

ODSC - Open Data Science

JULY 22, 2023

We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes. Here are some highlights from ODSC Europe 2023, including some pictures of speakers and attendees, popular talks, and a summary of what kept people busy.

Apache Kafka 52

Apache Kafka Machine Learning Machine Learning Data Science 52

Pickl AI

DECEMBER 9, 2024

What is Apache Hive? Hive is a data warehouse tool built on Hadoop that enables SQL-like querying to analyse large datasets. What are the Key Features of Apache Hive? Hive provides SQL-like querying, schema-on-read functionality, and compatibility with Hadoop for large-scale Data Analysis. How Did You Manage Them?

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

Pickl AI

NOVEMBER 4, 2024

Various types of storage options are available, including: Relational Databases: These databases use Structured Query Language (SQL) for data management and are ideal for handling structured data with well-defined relationships. SQL SQL is crucial for querying and managing relational databases.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Mlearning.ai

AUGUST 4, 2023

Apache Kafka and R abbitMQ are particularly popular in LEs. In LEs, alongside PostgreSQL , MySQL , Microsoft SQL Server , SQLite , MongoDB , and Redis also enjoy high patronage. Graph 7: Percentage of Programming Languages MiscTech Tools In Both LEs and SMEs: ‘. NET (5+) ’, ‘ pandas ’, ‘ numpy ’, and ‘. NET Framework (1.0–4.8)’

Database 52

Database Apache Kafka SQL AI 52

Pickl AI

OCTOBER 21, 2024

It manipulates data using SQL (Structured Query Language). It offers high performance and supports SQL queries, making it a modern solution for large-scale applications. Using Kafka, Twitter can effectively handle high-throughput data streams, enabling users to receive timely notifications and updates.

Database 52

Database Apache Kafka Machine Learning Machine Learning 52

AWS Machine Learning Blog

JANUARY 6, 2023

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. Amazon MSK makes it easy to ingest and process streaming data in real time with fully managed Apache Kafka.

AWS 80

AWS Data Warehouse ML ML 80

The MLOps Blog

MARCH 15, 2023

Typical examples include: Airbyte Talend Apache Kafka Apache Beam Apache Nifi While getting control over the process is an ideal position an organization wants to be in, the time and effort needed to build such systems are immense and frequently exceeds the license fee of a commercial offering. Cons Limited connectors.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

Pickl AI

JULY 8, 2024

Database Extraction: Retrieval from structured databases using query languages like SQL. Utilise in-memory data processing tools like Apache Kafka and Apache Flink, which provide low-latency data ingestion and processing capabilities. Web Scraping: Automated extraction from websites using scripts or specialised tools.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

DagsHub

APRIL 7, 2024

Thanks to its various operators, it is integrated with Python, Spark, Bash, SQL, and more. Also, while it is not a streaming solution, we can still use it for such a purpose if combined with systems such as Apache Kafka. This also means that it comes with a large community and comprehensive documentation.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

AUGUST 9, 2024

Understanding the differences between SQL and NoSQL databases is crucial for students. Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. APIs Understanding how to interact with Application Programming Interfaces (APIs) to gather data from external sources.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

DagsHub

OCTOBER 23, 2024

Here’s the structured equivalent of this same data in tabular form: With structured data, you can use query languages like SQL to extract and interpret information. Apache Kafka Apache Kafka is a distributed event streaming platform for real-time data pipelines and stream processing.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

phData

SEPTEMBER 27, 2024

Instead of simple SQL queries, we often need to use more complex temporal query languages or rely on derived views for simpler querying. Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. But the power of logs doesn’t stop there.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

Pickl AI

DECEMBER 4, 2024

Apache Kafka), organisations can now analyse vast amounts of data as it is generated. Grasp the Fundamentals of Data Analysis and Management Build a strong foundation in Data Analysis by learning data manipulation techniques using SQL and Excel. Focus on Python and R for Data Analysis, along with SQL for database management.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

MARCH 19, 2025

Tools like Python, SQL, Apache Spark, and Snowflake help engineers automate workflows and improve efficiency. Python, SQL, and Apache Spark are essential for data engineering workflows. Real-time data processing with Apache Kafka enables faster decision-making.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 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. Apache Kafka Overview Apache Kafka is an open-source stream-processing platform capable of handling trillions of events per day.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52