Data Engineering Podcast

SEPTEMBER 25, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

Food 100

Food MongoDB Scala MySQL 100

Data Engineering Podcast

JULY 3, 2022

In order to quickly identify if and how two data systems are out of sync Gleb Mezhanskiy and Simon Eskildsen partnered to create the open source data-diff utility. report having current investments in automation, 85% of data teams plan on investing in automation in the next 12 months. In fact, while only 3.5%

Data Integration 100

Data Integration MongoDB Scala MySQL 100

Data Engineering Podcast

OCTOBER 2, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. In fact, while only 3.5%

IT 100

IT Food PostgreSQL MongoDB 100

Data Engineering Podcast

AUGUST 6, 2022

Summary The optimal format for storage and retrieval of data is dependent on how it is going to be used. For analytical systems there are decades of investment in data warehouses and various modeling techniques. RudderStack helps you build a customer data platform on your warehouse or data lake.

Machine Learning 100

Machine Learning Database MySQL PostgreSQL 100

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

APRIL 25, 2023

Data engineers add meaning to the data for companies, be it by designing infrastructure or developing algorithms. The practice requires them to use a mix of various programming languages, data warehouses, and tools. While they go about it - enter big data data engineer tools.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. A loose schema allows for some data structure flexibility while maintaining a general organization. Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 14, 2023

As the volume and complexity of data continue to grow, organizations seek faster, more efficient, and cost-effective ways to manage and analyze data. In recent years, cloud-based data warehouses have revolutionized data processing with their advanced massively parallel processing (MPP) capabilities and SQL support.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Rockset

NOVEMBER 28, 2022

It works with existing streaming systems like Apache Kafka, Amazon Kinesis, and Azure Events Hubs, making it easier than ever to build a real-time data pipeline. Data warehouses were built for batch jobs, so we shouldn’t be surprised by this. This method has a handful of drawbacks. The upshot?

Data Warehouse 52

Data Warehouse PostgreSQL MongoDB Data Pipeline 52

Rockset

AUGUST 30, 2021

Apache Kafka has made acquiring real-time data more mainstream, but only a small sliver are turning batch analytics, run nightly, into real-time analytical dashboards with alerts and automatic anomaly detection. The majority are still draining streaming data into a data lake or a warehouse and are doing batch analytics.

SQL 52

SQL Kafka MongoDB MySQL 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

ProjectPro

AUGUST 24, 2021

Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

MAY 14, 2021

Big Data analytics encompasses the processes of collecting, processing, filtering/cleansing, and analyzing extensive datasets so that organizations can use them to develop, grow, and produce better products. Big Data analytics processes and tools. Data ingestion. Data storage and processing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Query Surge helps us automate our manual efforts in Big Data testing.

Big Data 52

Big Data Hadoop AWS Relational Database 52