Altexsoft

JANUARY 14, 2021

It is a home for an OLAP (online analytical processing) server that converts data into a form more suitable for analysis and querying. The top tier is referred to as the front-end or client layer. What specialists and their expertise level are required to handle a data warehouse? Data loading. Data loading.

Backup 115

Backup Azure Software Review Systems Review 115

Xebia

FEBRUARY 25, 2024

Data science is generally not operationalized Consider a data flow from a machine or process, all the way to an end-user. 2 In general, the flow of data from machine to the data engineer (1) is well operationalized. You could argue the same about the data engineering step (2) , although this differs per company.

Applications 130

Applications Technical Review Software Review Open Source 130

Perficient

AUGUST 2, 2023

As a senior technical consultant, I help clients better leverage their data. I assist and advise teams when migrating data and infrastructure to Google Cloud Platform (GCP). READ MORE : Perficient is a Google Cloud Premier Partner What is one of your proudest accomplishments professionally?

Technical Advisors 52

Technical Advisors Technical Review Google Cloud Culture 52

Capgemini

OCTOBER 10, 2024

Taking a RAG approach The retrieval-augmented generation (RAG) approach is a powerful technique that leverages the capabilities of Gen AI to make requirements engineering more efficient and effective. As a Google Cloud Partner , in this instance we refer to text-based Gemini 1.5 Pro, a large language model (LLM).

Artificial Inteligence 52

Artificial Inteligence Analysis Google Cloud Infrastructure 52

Confluent

OCTOBER 16, 2019

With tools like KSQL and Kafka Connect, the concept of streaming ETL is made accessible to a much wider audience of developers and data engineers. My source of data is a public feed provided by the UK’s Network Rail company through an ActiveMQ interface. There’s also some static reference data that is published on web pages. ?After

Data 19

Data Training Analytics Storage 19

CIO

JULY 14, 2023

To get good output, you need to create a data environment that can be consumed by the model,” he says. You need to have data engineering skills, and be able to recalibrate these models, so you probably need machine learning capabilities on your staff, and you need to be good at prompt engineering.

Generative AI 148

Generative AI Artificial Inteligence Open Source ChatGPT 148

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. Phases of the data migration process. Data sources and destinations.

Software Review 69

Software Review Software Data Technical Review 69

Altexsoft

AUGUST 25, 2021

Sentiment analysis results by Google Cloud Natural Language API. This includes the following problems in the dataset: Wrong formulted data values (same entities with different syntax, like September 4th and 4th of September ). Co-reference problems (the same person in the text can be called Oliver, Mr.Twist, the boy, he, etc.).

Tools 139

Tools Artificial Inteligence Technical Review Systems Review 139

Perficient

FEBRUARY 16, 2024

Reading Data: # Reading data from DBFS val data_df = spark.read.csv("dbfs:/FileStore/tables/Largest_earthquakes_by_year.csv") The code will read the specified CSV file into a DataFrame named data_df, allowing further processing and analysis using Spark’s DataFrame API.

System 52

System Storage Azure Big Data 52

Altexsoft

APRIL 26, 2022

Initially built on top of the Amazon Web Services (AWS), Snowflake is also available on Google Cloud and Microsoft Azure. As such, it is considered cloud-agnostic. Modern data pipeline with Snowflake technology as its part. BTW, we have an engaging video explaining how data engineering works.

Weak Development Team 59

Weak Development Team Data Storage Technical Review 59

Kentik

APRIL 11, 2016

This involves pre-selecting various combinations of dimensions/columns from the source data, and collapsing that data into multiple result sets that contain only those dimensions. Known as “multidimensional online analytical processing” (M-OLAP), this approach is sometimes referred to more succinctly as “data cubes.”

Big Data 40

Big Data Analytics Network Architecture 40

Existek

SEPTEMBER 28, 2023

Monitoring and maintenance: After deployment, AI software developers monitor the performance of the AI system, address arising issues, and update the model as needed to adapt to changing data distributions or business requirements. Specialists are often available to start work on the project quickly and at competitive rates.

Artificial Inteligence 52

Artificial Inteligence Development How To Technical Review 52

Daniel Bryant

SEPTEMBER 13, 2019

This event obviously consisted of a self-selected audience of HashiFans, but it’s still worth mentioning that there was a decided pushback in relation to an organisation attempting to select “one cloud to rule them” that I’ve heard at previous events.

Infrastructure 8

Infrastructure Azure Software Engineering Cloud 8

Cloudera

DECEMBER 12, 2018

Now you can just land those files and instead of having a separate filer that doesn’t have any compute processing in it, you can land them in a distributed file system like HDFS, which is generally co-located with a data processing engine like Impala. Greg Rahn: I refer to this as friction-free data landing.

Marketing 42

Marketing Data Storage Big Data 42

O'Reilly Media - Ideas

MARCH 1, 2023

Data Data is another very broad category, encompassing everything from traditional business analytics to artificial intelligence. Data engineering was the dominant topic by far, growing 35% year over year. Data engineering deals with the problem of storing data at scale and delivering that data to applications.

Trends 144

Trends Technical Review Technology Software Review 144

O'Reilly Media - Ideas

JANUARY 25, 2022

A quick look at bigram usage (word pairs) doesn’t really distinguish between “data science,” “data engineering,” “data analysis,” and other terms; the most common word pair with “data” is “data governance,” followed by “data science.” It’s clear that Amazon Web Services’ competition is on the rise.

Trends 117

Trends Technical Review Technology Artificial Inteligence 117

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. How data engineering works under the hood.

Big Data 59

Big Data Data Google Cloud Open Source 59

Battery Ventures

OCTOBER 7, 2020

This has all translated into some prominent initial-public offerings for cloud-native companies this year—deals few could have imagined during the initial shock of the pandemic in March and April. Today, we delve deeper into these topics in our “State of the Cloud 2020” report.

Open Source 144

Open Source Cloud Google Cloud Azure 144

CIO

JANUARY 29, 2025

Large enterprises have long used knowledge graphs to better understand underlying relationships between data points, but these graphs are difficult to build and maintain, requiring effort on the part of developers, data engineers, and subject matter experts who know what the data actually means.

Artificial Inteligence 202

Artificial Inteligence Enterprise Open Source Research 202