Trigent

JANUARY 18, 2023

Technologies such as serverless cloud technology, Product, Quality, and Data engineering, to name a few, have minimized development costs and improved productivity and scalability with ease of customization. The recognition stands as a support to developing trust and authenticity within the B2B community.

Software Review 52

Software Review Technical Review Systems Review Software 52

Altexsoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Weak Development Team 64

Weak Development Team Machine Learning Artificial Inteligence Software Review 64

Altexsoft

DECEMBER 4, 2020

Three types of data migration tools. Automation scripts can be written by data engineers or ETL developers in charge of your migration project. This makes sense when you move a relatively small amount of data and deal with simple requirements. Use cases: moving data from on-premises to cloud or between cloud environments.

Software Review 69

Software Review Software Data Technical Review 69

CIO

JULY 29, 2022

For example, if a data team member wants to increase their skills or move to a data engineer position, they can embark on a curriculum for up to two years to gain the right skills and experience. The bootcamp broadened my understanding of key concepts in data engineering.

Groups 229

Groups Security Development Data Engineering 229

Altexsoft

NOVEMBER 5, 2021

Health information management (HIM) is a set of practices to organize medical data so that it can be effectively used for enhancing the quality of care. It aims at making the right health content accessible whenever it’s required, at the same time ensuring its high quality and security. Areas HIM takes care of.

Technical Review 59

Technical Review Technology Software Review Healthcare 59

Altexsoft

OCTOBER 21, 2022

It offers high throughput, low latency, and scalability that meets the requirements of Big Data. The technology was written in Java and Scala in LinkedIn to solve the internal problem of managing continuous data flows. All data goes through the middleman — in our case, Kafka — that manages messages and ensures their security.

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

Altexsoft

APRIL 26, 2022

With the consistent rise in data volume, variety, and velocity, organizations started seeking special solutions to store and process the information tsunami. This demand gave birth to cloud data warehouses that offer flexibility, scalability, and high performance. Adequate security and data protection.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

O'Reilly Media - Ideas

MARCH 1, 2023

It’s gratifying when we see an important topic come alive: zero trust, which reflects an important rethinking of how security works, showed tremendous growth. Software development is followed by IT operations (18%), which includes cloud, and by data (17%), which includes machine learning and artificial intelligence.

Trends 133

Trends Technical Review Technology Software Review 133

Altexsoft

JULY 29, 2022

What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop? Under the hood, the framework divides a chunk of Big Data into smaller, digestible parts and allocates them across multiple commodity machines to be processed in parallel. Scalability. Apache Hadoop architecture.

Big Data 59

Big Data Data Google Cloud Storage 59

Kentik

SEPTEMBER 11, 2015

FDW backends can be a surprisingly powerful tool when your data model isn’t classically relational but you still want all the nice things that come with PostgreSQL (aggregates, client libraries, authentication, group by, etc.). Once things are installed, create a new table by installing the FWD extension (actually a.so

Data 40

Data Authentication Data Engineering Scalability 40

DataRobot

MARCH 16, 2023

To work effectively, data scientists need agility in the form of access to enterprise data, streamlined tooling, and infrastructure that just works. Agility and enterprise security, compliance, and governance are often at odds. The prototyping loop, particularly the ML data prep for each new experiment, is tedious at best.

Data 52

Data Machine Learning Artificial Inteligence Agile 52

Cloudera

DECEMBER 15, 2022

With a common interface in CDP that works across different cloud service providers, you can break down data silos while ensuring consistent security, governance, and traceability, all while seamlessly moving your Apache Iceberg – based workloads across deployment environments frictionlessly. Performance and scalability.

Cloud 76

Cloud Data Analytics Machine Learning 76

Cloudera

AUGUST 20, 2021

The Cloudera Data Platform comprises a number of ‘data experiences’ each delivering a distinct analytical capability using one or more purposely-built Apache open source projects such as Apache Spark for Data Engineering and Apache HBase for Operational Database workloads. A Robust Security Framework.

Strategy 94

Strategy Data Technical Review Weak Development Team 94

Cloudera

DECEMBER 14, 2020

Today, a new modern data platform is here to transform how businesses take advantage of real-time analytics. Cloudera Data Platform (CDP) is the new data cloud built for the enterprise. Apache Kafka helps data administrators and streaming app developers to buffer high volumes of streaming data for high scalability.

Analytics 68

Analytics Big Data Government Cloud 68

Cloudera

FEBRUARY 14, 2022

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of. Usage Patterns.

Data Engineering 109

Data Engineering Engineering Data Storage 109

Cloudera

FEBRUARY 22, 2021

Providing a comprehensive set of diverse analytical frameworks for different use cases across the data lifecycle (data streaming, data engineering, data warehousing, operational database and machine learning) while at the same time seamlessly integrating data content via the Shared Data Experience (SDX), a layer that separates compute and storage.

Data 76

Data Analytics Government Technical Review 76