Aggregated Data and NoSQL - Data Engineering Digest

Aggregated Data

NoSQL

Case Study: Is Your NoSQL Data Hindering Real-Time Analytics? Savvy Solved It with Rockset.

Rockset

JULY 21, 2022

All interactions are streamed in the form of semi-structured events into Firebase’s NoSQL cloud database, where the data, which includes a large number of nested objects and arrays, is ingested. The Reporting View , which displays charts with aggregate data on visitors such as number of visitors per day, or visitors by source.

NoSQL

NoSQL IT MongoDB SQL

Most important Data Engineering Concepts and Tools for Data Scientists

DareData

JANUARY 30, 2023

For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production. Examples of NoSQL databases include MongoDB or Cassandra.

Data Engineer

Data Engineer Data Engineering NoSQL Engineering

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Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Rockset

FEBRUARY 2, 2022

Developers choose this database because of its flexible data model and its inherent scalability as a NoSQL database. Yet, analytics is now a vital part of modern data applications. The benefit of these tools is that they’re built specifically for data analytics. The downsides of data warehouses are data and query latency.

MongoDB

MongoDB NoSQL Data Warehouse BI

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

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ELT Explained: What You Need to Know

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data

Raw Data Data Warehouse Data Cleanse Data Integration

The Good and the Bad of the Elasticsearch Search and Analytics Engine

AltexSoft

SEPTEMBER 21, 2023

In this edition of “The Good and The Bad” series, we’ll dig deep into Elasticsearch — breaking down its functionalities, advantages, and limitations to help you decide if it’s the right tool for your data-driven aspirations. What is Elasticsearch? It is developed in Java and built upon the highly reputable Apache Lucene library.

Engineering

Engineering NoSQL Programming Language Java

Python for Data Engineering

Ascend.io

SEPTEMBER 14, 2023

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

Data Engineer

Data Engineer Data Engineering Python Engineering

Case Study: How Rockset's Real-Time Analytics Platform Propels the Growth of Our NFT Marketplace

Rockset

OCTOBER 26, 2022

Also, DynamoDB, as a NoSQL database, doesn’t support SQL commands such as JOINING multiple tables. One was to create another data pipeline that would aggregate data as it was ingested into DynamoDB. That’s where DynamoDB’s analytical limitations reared their ugly heads.

SQL

SQL NoSQL Database Aggregated Data

Real-Time Analytics on DynamoDB - Using DynamoDB Streams with Lambda and ElastiCache

Rockset

AUGUST 12, 2019

Low data latency requirements rule out ETL-based solutions which increase your data latency above the real-time threshold and inevitably lead to “ETL hell”. DynamoDB is a fully managed NoSQL database provided by AWS that is optimized for point lookups and small range scans using a partition key.

NoSQL

NoSQL AWS SQL Database

14 Best Database Certifications in 2023 to Boost Your Career

Knowledge Hut

SEPTEMBER 6, 2023

Over the past decade, the IT world transformed with a data revolution. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it. Skills acquired : Relational database concepts Retrieving data using the SQL SELECT statement.

Database

Database Certification MongoDB MySQL

ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

AltexSoft

DECEMBER 23, 2022

Both incremental patterns are often used when the goal is to keep a local copy of the information up-to-date, or when the data source is very large and extracting all of the data would be impractical. The “load” phase involves loading the extracted data into a central repository, such as a data warehouse or data lake.

Process

Process Building Raw Data Data Lake

The Good and the Bad of Apache Kafka Streaming Platform

AltexSoft

OCTOBER 21, 2022

This enables systems using Kafka to aggregate data from many sources and to make it consistent. Instead of interfering with each other, Kafka consumers create groups and split data among themselves. cloud data warehouses — for example, Snowflake , Google BigQuery, and Amazon Redshift.

Kafka

Kafka Hadoop Big Data ETL Tools

DynamoDB Filtering and Aggregation Queries Using SQL on Rockset

Rockset

SEPTEMBER 13, 2022

Further, data is king, and users want to be able to slice and dice aggregated data as needed to find insights. Users don't want to wait for data engineers to provision new indexes or build new ETL chains. They want unfettered access to the freshest data available. DynamoDB is a NoSQL database provided by AWS.

SQL

SQL Database Relational Database NoSQL

20 Best Open Source Big Data Projects to Contribute on GitHub

ProjectPro

NOVEMBER 15, 2021

It was built from the ground up for interactive analytics and can scale to the size of Facebook while approaching the speed of commercial data warehouses. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data

Big Data Project Metadata Programming Language

Sqoop vs. Flume Battle of the Hadoop ETL tools

ProjectPro

OCTOBER 28, 2015

Flume functions well in streaming data sources which are generated continuously in hadoop environment such as log files from multiple servers whereas Apache Sqoop is designed to work well with any kind of relational database system that has JDBC connectivity.

ETL Tools

ETL Tools Hadoop Relational Database Unstructured Data

100+ Data Engineer Interview Questions and Answers for 2023

ProjectPro

JULY 27, 2021

Also, acquire a solid knowledge of databases such as the NoSQL or Oracle database. Questions addressing data modeling and database architecture test your understanding of entity-relationship modeling, normalization and denormalization, dimensional modeling, and relevant ideas. What are the daily responsibilities of a data engineer?

Data Engineer

Data Engineer Data Engineering Engineering Hadoop

Top Big Data Hadoop Projects for Practice with Source Code

ProjectPro

APRIL 20, 2017

There are various kinds of hadoop projects that professionals can choose to work on which can be around data collection and aggregation, data processing, data transformation or visualization. How small file problems in streaming can be resolved using a NoSQL database. Using Flume to handle small files in streaming.

Hadoop

Hadoop Big Data Coding Project

Handling Out-of-Order Data in Real-Time Analytics Applications

Rockset

APRIL 15, 2022

Rockset not only continuously ingests data, but also can “rollup” the data as it is being generated. By using SQL to aggregate data as it is being ingested, this greatly reduces the amount of data stored (5-150x) as well as the amount of compute needed queries (boosting performance 30-100x).

Analytics Application

Analytics Application Data Warehouse Kafka Raw Data

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

AltexSoft

MARCH 14, 2023

Databases store key information that powers a company’s product, such as user data and product data. The ones that keep only relational data in a tabular format are called SQL or relational database management systems (RDBMSs). Joining: combining data from multiple sources based on a common key or attribute.

IT Data Warehouse Data Governance Data Lake

Case Study: Is Your NoSQL Data Hindering Real-Time Analytics? Savvy Solved It with Rockset.

Most important Data Engineering Concepts and Tools for Data Scientists

Webinars

Trending Sources

Five Ways to Run Analytics on MongoDB – Their Pros and Cons

Webinars

ELT Explained: What You Need to Know

The Good and the Bad of the Elasticsearch Search and Analytics Engine

Python for Data Engineering

Case Study: How Rockset's Real-Time Analytics Platform Propels the Growth of Our NFT Marketplace

Real-Time Analytics on DynamoDB - Using DynamoDB Streams with Lambda and ElastiCache

14 Best Database Certifications in 2023 to Boost Your Career

ELT Process: Key Components, Benefits, and Tools to Build ELT Pipelines

The Good and the Bad of Apache Kafka Streaming Platform

DynamoDB Filtering and Aggregation Queries Using SQL on Rockset

20 Best Open Source Big Data Projects to Contribute on GitHub

Sqoop vs. Flume Battle of the Hadoop ETL tools

100+ Data Engineer Interview Questions and Answers for 2023

Top Big Data Hadoop Projects for Practice with Source Code

Handling Out-of-Order Data in Real-Time Analytics Applications

The Modern Data Stack: What It Is, How It Works, Use Cases, and Ways to Implement

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