Data Science Dojo

JULY 3, 2024

Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python. Databases and SQL : Managing and querying relational databases using SQL, as well as working with NoSQL databases like MongoDB.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Analytics Vidhya

FEBRUARY 20, 2023

Introduction Azure data factory (ADF) is a cloud-based data ingestion and ETL (Extract, Transform, Load) tool. The data-driven workflow in ADF orchestrates and automates data movement and data transformation.

Azure 283

Azure ETL Analytics Analytics 283

The MLOps Blog

JUNE 27, 2023

It integrates with Git and provides a Git-like interface for data versioning, allowing you to track changes, manage branches, and collaborate with data teams effectively. Dolt Dolt is an open-source relational database system built on Git. It could help you detect and prevent data pipeline failures, data drift, and anomalies.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. This section explores essential aspects of Data Engineering.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Precisely

JANUARY 19, 2023

Yet mainframes weren’t designed to integrate easily with modern distributed computing platforms. Cloud computing, object-oriented programming, open source software, and microservices came about long after mainframes had established themselves as a mature and highly dependable platform for business applications.

AWS 52

AWS Cloud Computing Data Pipeline Big Data 52

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Precisely

APRIL 6, 2023

That creates new challenges in data management and analytics. Each new system comes with its own schema, which must be mapped and normalized alongside other data. The best integration tools make it easy to build and deploy data pipelines to accommodate the ever-changing needs of modern financial services organizations.

Data Quality 52

Data Quality Data Pipeline Analytics Analytics 52

phData

OCTOBER 12, 2023

When the data or pipeline configuration needs to be changed, tools like Fivetran and dbt reduce the time required to make the change, and increase the confidence your team can have around the change. These allow you to scale your pipelines quickly. Governance When talking about scaling, governance doesn’t often come up.

Data Warehouse 52

Data Warehouse Database Cloud Data Data Pipeline 52

Alation

JANUARY 17, 2023

These tools are used to manage big data, which is defined as data that is too large or complex to be processed by traditional means. How Did the Modern Data Stack Get Started? The rise of cloud computing and cloud data warehousing has catalyzed the growth of the modern data stack.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Snowflake Database Pros Extensive Storage Opportunities Snowflake provides affordability, scalability, and a user-friendly interface.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

phData

JANUARY 15, 2024

Access Controls and User Authentication Access control regulates who can interact with various database objects, such as tables, views, and functions. In Snowflake, securable objects (representing database resources) are controlled through roles. HITRUST: Meeting stringent standards for safeguarding healthcare data.

Data Governance 52

Data Governance Database Data Warehouse Cloud Computing 52

Alation

APRIL 14, 2022

A cloud-ready data discovery process can ease your transition to cloud computing and streamline processes upon arrival. So how do you take full advantage of the cloud? Migration leaders would be wise to enable all the enhancements a cloud environment offers, including: Special requirements for AI/ML.

Data Governance 59

Data Governance ML ML Cloud Data 59

phData

MAY 25, 2023

Snowflake is a cloud computing–based data cloud company that provides data warehousing services that are far more scalable and flexible than traditional data warehousing products. Importing data allows you to ingest a copy of the source data into an in-memory database.

Power BI 84

Power BI Analytics Analytics Azure 84

phData

JANUARY 5, 2024

Understanding the Cost of Snowflake Like any other cloud computing tool, costs can quickly add up if not kept in check. The total cost of using Snowflake is the aggregate of the cost of using data transfer, storage, and computing resources.

Power BI 52

Power BI Cloud Computing Data Pipeline AWS 52

Pickl AI

SEPTEMBER 5, 2024

By leveraging Azure’s capabilities, you can gain the skills and experience needed to excel in this dynamic field and contribute to cutting-edge data solutions. Microsoft Azure, often referred to as Azure, is a robust cloud computing platform developed by Microsoft. What is Azure?

Azure 52

Azure Data Scientist Data Science Machine Learning 52

IBM Journey to AI blog

FEBRUARY 9, 2024

But the most impactful developments may be those focused on governance, middleware, training techniques and data pipelines that make generative AI more trustworthy , sustainable and accessible, for enterprises and end users alike. Here are some important current AI trends to look out for in the coming year.

AI 119

AI AI Artificial Intelligence Artificial Intelligence 119

AWS Machine Learning Blog

DECEMBER 18, 2024

The deduplication process involved embedding dataset elements using a text embedder, then computing cosine similarity between the embeddings to identify similar elements. He has worked on projects in different domains, including MLOps, computer vision, and NLP, involving a broad set of AWS services.

Clustering 102

Clustering AWS AI AI 102