Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices. Plus, there’s the _delta_log folder.

Big Data 71

Big Data Data Data Storage SQL 71

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing.

Data Management 52

Data Management Data Lake Management Data Governance 52

Knowledge Hut

NOVEMBER 3, 2023

Skills Required for MongoDB for Data Science To excel in MongoDB for data science, you need a combination of technical and analytical skills: Database Querying: It is necessary to know how to write sophisticated queries using the query language of MongoDB. Quickly pull (fetch), filter, and reduce data.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Towards Data Science

NOVEMBER 4, 2023

Back in October, I wrote about the rise of the Data Engineer, the role, its challenges, responsibilities, daily routine and how to become successful in this field. The data engineering landscape is constantly changing but major trends seem to remain the same. So here are a few things to consider that can help us answer these questions.

Data Engineering 83

Data Engineering Data Engineer Engineering BI 83

AltexSoft

OCTOBER 3, 2022

While DBpedia uses Wikipedia data to enrich the graph, the Wikidata graph developed and launched in 2012 is designed to store knowledge that will be used already in Wikipedia (mostly for filling infoboxes and tables on the page) in many available languages. Knowledge graphs for enterprise data integration.

Relational Database 52

Relational Database Banking Media Computer Science 52

Striim

NOVEMBER 8, 2023

This allows for two-way integration so that information can flow from one system to another in real-time. Striim is a cloud-native Data Mesh platform that offers features such as automated data mapping, real-time data integration, streaming analytics, and more.

Architecture 52

Architecture Generalist Government Datasets 52

Netflix Tech

OCTOBER 27, 2020

For example, in order to enhance our user experience, one online application fetches subscribers’ preferences data to recommend movies and TV shows. The data warehouse is not designed to serve point requests from microservices with low latency. Dataset of January 1st 2020. D ataset of January 2nd 2020.

Data Warehouse 97

Data Warehouse Datasets Data Big Data 97

Monte Carlo

FEBRUARY 6, 2023

In this post, we’ll examine some best practices for migrating your data to a cloud solution, show you how to develop your own migration strategy, and take a closer look at some popular cloud warehouse solutions that you might consider for your platform. Facilitating self-service data? Integrating new tooling? Let’s jump in!

Data Warehouse 52

Data Warehouse AWS Data Validation Data 52

dbt Developer Hub

FEBRUARY 7, 2022

To do so, we’ll focus on three steps: Performing the email domain extraction from the email Flagging personal emails Creating a column for corporate emails After we complete these steps, we’ll also cover a "human in the loop" step to ensure data integrity at the modelling stage.

Data Warehouse 52

Data Warehouse Datasets Data SQL 52

ProjectPro

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. No reliability exists.

Big Data 52

Big Data Hadoop AWS Relational Database 52