Data Science 101

NOVEMBER 7, 2019

Azure Synapse. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Synapse allows one to use SQL to query petabytes of data, both relational and non-relational, with amazing speed. R Support for Azure Machine Learning. Azure Quantum.

Data Science 106

Data Science Azure SQL Machine Learning 106

Women in Big Data

NOVEMBER 27, 2024

Optimized for analytical processing, it uses specialized data models to enhance query performance and is often integrated with business intelligence tools, allowing users to create reports and visualizations that inform organizational strategies.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

Tableau

MARCH 29, 2021

we’ve added new connectors to help our customers access more data in Azure than ever before: an Azure SQL Database connector and an Azure Data Lake Storage Gen2 connector. As our customers increasingly adopt the cloud, we continue to make investments that ensure they can access their data anywhere.

Azure 52

Azure Tableau Data Lakes SQL 52

phData

NOVEMBER 8, 2024

Note : Cloud Data warehouses like Snowflake and Big Query already have a default time travel feature. However, this feature becomes an absolute must-have if you are operating your analytics on top of your data lake or lakehouse. It can also be integrated into major data platforms like Snowflake.

Data Lakes 52

Data Lakes Data Warehouse Database Azure 52

ODSC - Open Data Science

JUNE 1, 2023

Real-Time ML with Spark and SBERT, AI Coding Assistants, Data Lake Vendors, and ODSC East Highlights Getting Up to Speed on Real-Time Machine Learning with Spark and SBERT Learn more about real-time machine learning by using this approach that uses Apache Spark and SBERT. Well, these libraries will give you a solid start.

Data Lakes 52

Data Lakes ML ML Citizen Data Scientist 52

Pickl AI

DECEMBER 2, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Summary: Big Data encompasses vast amounts of structured and unstructured data from various sources. Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Key Takeaways Big Data originates from diverse sources, including IoT and social media.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

APRIL 6, 2023

Accordingly, one of the most demanding roles is that of Azure Data Engineer Jobs that you might be interested in. The following blog will help you know about the Azure Data Engineering Job Description, salary, and certification course. How to Become an Azure Data Engineer?

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

Pickl AI

SEPTEMBER 5, 2024

Summary: This blog provides a comprehensive roadmap for aspiring Azure Data Scientists, outlining the essential skills, certifications, and steps to build a successful career in Data Science using Microsoft Azure. What is Azure?

Azure 52

Azure Data Scientist Data Science Machine Learning 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. However, these tools have functional gaps for more advanced data workflows. This can also make the learning process challenging.

Machine Learning 98

Machine Learning Machine Learning Data Lakes Database 98

Dataconomy

SEPTEMBER 4, 2023

Big data analytics: Big data analytics is designed to handle massive volumes of data from various sources, including structured and unstructured data. Big data analytics is essential for organizations dealing with large-scale data, such as social media platforms, e-commerce giants, and scientific research.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

ODSC - Open Data Science

FEBRUARY 2, 2023

Big Data As datasets become larger and more complex, knowing how to work with them will be key. Big data isn’t an abstract concept anymore, as so much data comes from social media, healthcare data, and customer records, so knowing how to parse all of that is needed.

Data Science 98

Data Science Data Scientist Computer Science Computer Science 98

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. DataRobot Data Prep. free trial.

Data Lakes 52

Data Lakes Azure Data Pipeline Hadoop 52

ODSC - Open Data Science

APRIL 3, 2023

Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis. Competence in data quality, databases, and ETL (Extract, Transform, Load) are essential. Cloud Services: Google Cloud Platform, AWS, Azure.

Analytics 52

Analytics Analytics Data Analyst Data Science 52

Pickl AI

NOVEMBER 4, 2024

Introduction Data Engineering is the backbone of the data-driven world, transforming raw data into actionable insights. As organisations increasingly rely on data to drive decision-making, understanding the fundamentals of Data Engineering becomes essential. million by 2028.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JULY 6, 2023

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. Processing of Data Once the data is stored, Hive provides a metadata layer allowing users to define the schema and create tables.

Hadoop 52

Hadoop SQL Big Data Big Data 52

The MLOps Blog

JUNE 27, 2023

Microsoft Azure ML Platform The Azure Machine Learning platform provides a collaborative workspace that supports various programming languages and frameworks. Databricks Databricks is a cloud-native platform for big data processing, machine learning, and analytics built using the Data Lakehouse architecture.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

DagsHub

NOVEMBER 11, 2024

These processes are essential in AI-based big data analytics and decision-making. Data Lakes Data lakes are crucial in effectively handling unstructured data for AI applications. It acts as a common ground wherein data is systematically collected, integrated, and processed in an efficient manner.

AI 52

AI AI Data Lakes Database 52

ODSC - Open Data Science

OCTOBER 20, 2023

At the AI Expo and Demo Hall as part of ODSC West in a few weeks, you’ll have the opportunity to meet one-on-one with representatives from industry-leading organizations like Microsoft Azure, Hewlett Packard, Iguazio, neo4j, Tangent Works, Qwak, Cloudera, and others.

AI 52

AI AI Data Science Machine Learning 52

Pickl AI

MARCH 10, 2025

Scalability for Large Datasets Power BI can handle massive datasets efficiently using its in-memory analytics engine and Azure integration. Example: A manufacturing company analyses sensor data from production facilities to predict equipment failures and optimise operations. Is Power BI Suitable for Small Businesses?

Power BI 52

Power BI Business Intelligence Business Intelligence Analytics 52

DagsHub

OCTOBER 23, 2024

To combine the collected data, you can integrate different data producers into a data lake as a repository. A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Data Cleaning The next step is to clean the data after ingesting it into the data lake.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Alation

APRIL 14, 2022

This two-part series will explore how data discovery, fragmented data governance , ongoing data drift, and the need for ML explainability can all be overcome with a data catalog for accurate data and metadata record keeping. The Cloud Data Migration Challenge.

Data Governance 59

Data Governance ML ML Cloud Data 59

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Die Definition eines Data Lakehouse Ein Data Lakehouse ist eine moderne Datenspeicher- und -verarbeitungsarchitektur, die die Vorteile von Data Lakes und Data Warehouses vereint.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Towards AI

NOVEMBER 15, 2024

Image by author Hello Welcome to the Azure Data Engineer Project Series, Before building the Data Architecture or any data pipelines in any cloud platform, we need to know the basic terms each platform uses and how the platform will work. Here is the data pipeline building from ADLS to Azure SQL DB.

Azure 111

Azure Data Engineering Data Engineering Data Engineer 111

Pickl AI

FEBRUARY 23, 2025

Summary: Big Data tools empower organizations to analyze vast datasets, leading to improved decision-making and operational efficiency. Ultimately, leveraging Big Data analytics provides a competitive advantage and drives innovation across various industries.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52