Dataconomy

SEPTEMBER 27, 2023

The Microsoft Certified Solutions Associate and Microsoft Certified Solutions Expert certifications cover a wide range of topics related to Microsoft’s technology suite, including Windows operating systems, Azure cloud computing, Office productivity software, Visual Studio programming tools, and SQL Server databases.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

phData

JULY 17, 2023

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. Designed to cheaply and efficiently process large quantities of data.

Data Warehouse 52

Data Warehouse Data Pipeline Cloud Data ETL 52

AWS Machine Learning Blog

JULY 17, 2023

Amazon Redshift is a fully managed, fast, secure, and scalable cloud data warehouse. Organizations often want to use SageMaker Studio to get predictions from data stored in a data warehouse such as Amazon Redshift. This should return the records successfully for further data processing and analysis.

Clustering 94

Clustering AWS ML ML 94

phData

JUNE 14, 2023

which play a crucial role in building end-to-end data pipelines, to be included in your CI/CD pipelines. A common approach for versioning database changes is to record each change as a migration script and maintain it under version control. Additionally, we need to incorporate Flyway variables into the Flyway configuration file.

Data Pipeline 52

Data Pipeline Database SQL Data Engineer 52

Mlearning.ai

JULY 10, 2023

In prior to creating your first Scheduled Query, I recommend that you confirm with your database administrator that you have the adequate IAM permissions to create one. To create a Scheduled Query, the initial step is to ensure your SQL is accurately entered in the Query Editor. Creating Scheduled Queries is straightforward.

SQL 52

SQL Database Database Administration Data Lakes 52

The MLOps Blog

JANUARY 23, 2023

However, there are some key differences that we need to consider: Size and complexity of the data In machine learning, we are often working with much larger data. Basically, every machine learning project needs data. Given the range of tools and data types, a separate data versioning logic will be necessary.

ML 52

ML ML Data Lakes Machine Learning 52

Smart Data Collective

JUNE 6, 2021

Google BigQuery is a service (within the Google Cloud platform (GCP)) implemented to collect and analyze big data (also known as a data warehouse). It was released in 2011 and praised for its serverless architecture that enables highly scalable and fast-provided structured query language (SQL) analytics. What is Big Data?”

Big Data Analytics 137

Big Data Analytics Big Data Analytics Big Data Big Data 137