ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

AWS 98

AWS Scala Metadata Data Lake 98

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you. Why Use MongoDB for Data Science?

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Knowledge Hut

MARCH 22, 2024

Versatility: The versatile nature of MongoDB enables it to easily deal with a broad spectrum of data types , structured and unstructured, and therefore, it is perfect for modern applications that need flexible data schemas. Designing and implementing RESTful APIs for MongoDB data access.

MongoDB 52

MongoDB Amazon Web Services Computer Science Education 52

Striim

NOVEMBER 8, 2023

By exploring the benefits of using Data Mesh for your event streaming architecture, this article will help you decide if it’s the right solution for your organization. What is a Data Mesh and how does it work? It enables data to be accessed, transferred, and used in various ways such as creating dashboards or running analytics.

Architecture 52

Architecture Generalist Government Datasets 52

Knowledge Hut

APRIL 23, 2024

In the modern data-driven landscape, organizations continuously explore avenues to derive meaningful insights from the immense volume of information available. Two popular approaches that have emerged in recent years are data warehouse and big data. Data warehousing offers several advantages.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Rockset

OCTOBER 6, 2022

Consequently, we needed a data backend with the following characteristics: Scale With ~50 commits per working day (and thus at least 50 pull request updates per day) and each commit running over one million tests, you can imagine the storage/computation required to upload and process all our data. What did we use before Rockset?

AWS 52

AWS Data Schemas Accessible Accessibility 52

Rockset

SEPTEMBER 20, 2022

However, analyzing the data generated on the blockchain by these dApps is challenging. The appeal of blockchain - namely, open access, permissionless access, privacy and transparency - renders the on-chain data relatively basic, with only simple transaction details recorded.

PostgreSQL 52

PostgreSQL MongoDB SQL Datasets 52

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. A fundamental requirement for any lasting data system is that it should scale along with the growth of the business applications it wishes to serve.

Media 94

Media Database Metadata Data Schemas 94

Monte Carlo

JUNE 28, 2022

Over the past several years, cloud data lakes like Databricks have gotten so powerful (and popular) that according to Mordor Intelligence , the data lake market is expected to grow from $3.74 Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Cloud Academy

JANUARY 27, 2022

Data engineers are responsible for transforming data into an easily accessible format, identifying trends in data sets, and creating algorithms to make the raw data more useful for business units. Data engineers have the ability to convert raw data into useful insights.

Data Engineering 52

Data Engineering Data Engineer Certification Engineering 52

Monte Carlo

APRIL 20, 2023

What are the data lineage use cases and best practices that will drive value for the business? Validate data It works in the other direction as well. Let’s say I’m a data analyst reviewing data within the client_hub dashboard. With data lineage, I can look upstream and ensure no one made the “ You’re Using THAT table?!

Data Warehouse 52

Data Warehouse BI Data Government 52

ProjectPro

JANUARY 31, 2023

Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Big data analytics analyzes structured and unstructured data to generate meaningful insights based on changing market trends, hidden patterns, and correlations. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Pinterest Engineering

MAY 2, 2023

Therefore, our most important requirement for our storage layer was to be able to handle inserts. Therefore, it was imperative that the storage layer is able to handle out-of-order inserts. Cost Efficient Storage In the ML world, there is no gain that can be sustained without taking care of the cost. Handles duplicate values.

Lambda Architecture 66

Lambda Architecture Datasets Software Engineer Software Engineering 66

ProjectPro

NOVEMBER 22, 2021

According to the Businesswire report , the worldwide big data as a service market is estimated to grow at a CAGR of 36.9% Currently, there are over 32k+ big data jobs in the US, and the number is expected to keep growing with time. Is PySpark a Big Data tool? from 2019 to 2026, reaching $61.42 billion by 2026.

Hadoop 52

Hadoop Python Datasets Metadata 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40