Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Azure Quantum.

Data Science 106

Data Science Azure SQL Machine Learning 106

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Smart Data Collective

APRIL 29, 2020

Usually the term refers to the practices, techniques and tools that allow access and delivery through different fields and data structures in an organisation. Data management approaches are varied and may be categorised in the following: Cloud data management. Master data management. Data transformation.

Data Warehouse 83

Data Warehouse SQL Azure ETL 83

DataRobot Blog

MARCH 28, 2023

When it comes to deployment , the DataRobot AI Platform gives you the ultimate flexibility and choice when it comes to how you want to modernize – whether that’s on AWS , Google Cloud or Azure , single-tenant SaaS, on premises or hybrid deployment models – the choice is yours.

AI 52

AI AI Azure Data Warehouse 52

phData

MAY 25, 2023

One big issue that contributes to this resistance is that although Snowflake is a great cloud data warehousing platform, Microsoft has a data warehousing tool of its own called Synapse. In a perfect world, Microsoft would have clients push even more storage and compute to its Azure Synapse platform.

Power BI 84

Power BI Analytics Analytics Azure 84

ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Dataconomy

SEPTEMBER 4, 2023

Dependency on service providers : Relying on third-party cloud service providers means your operations are dependent on their uptime and reliability. Downtime, like the AWS outage in 2017 that affected several high-profile websites, can disrupt business operations. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse SQL Analytics Analytics 52

IBM Journey to AI blog

SEPTEMBER 11, 2023

Db2 can run on Red Hat OpenShift and Kubernetes environments, ROSA & EKS on AWS, and ARO & AKS on Azure deployments. Customers can also choose to run IBM Db2 database and IBM Db2 Warehouse as a fully managed service. Db2 database SaaS is a fully managed service for a high – performance, transactional workload.

Database 88

Database SQL Data Warehouse Machine Learning 88

The MLOps Blog

MAY 17, 2023

Focus Area ETL helps to transform the raw data into a structured format that can be easily available for data scientists to create models and interpret for any data-driven decision. A data pipeline is created with the focus of transferring data from a variety of sources into a data warehouse.

ETL 59

ETL Data Pipeline ML ML 59

IBM Journey to AI blog

AUGUST 3, 2023

IBM Security® Guardium® Data Protection empowers security teams to safeguard sensitive data through discovery and classification, data activity monitoring, vulnerability assessments and advanced threat detection.

Azure 59

Azure Database Natural Language Processing Analytics 59

Analytics Vidhya

OCTOBER 25, 2023

Introduction Struggling with expanding a business database due to storage, management, and data accessibility issues? To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023.

Database 208

Database Analytics Analytics Data Warehouse 208

Alation

FEBRUARY 8, 2022

The three technology planes of a self-service data mesh are: Plane 1: Data Infrastructure Plane. Examples include public cloud vendors like AWS, Azure, and GCP. Plane 2: Data Product Developer Experience Plane. Addresses networking, storage, access control. Plane 3: Mesh Supervision Plane.

Data Governance 52

Data Governance Data Engineering Data Engineer Data Engineering 52