Altexsoft

OCTOBER 30, 2021

If you’re an executive who has a hard time understanding the underlying processes of data science and get confused with terminology, keep reading. We will try to answer your questions and explain how two critical data jobs are different and where they overlap. Data science vs data engineering.

Data Engineering 98

Data Engineering Engineering Data Artificial Inteligence 98

Apiumhub

DECEMBER 9, 2024

Azure Key Vault Secrets integration with Azure Synapse Analytics enhances protection by securely storing and dealing with connection strings and credentials, permitting Azure Synapse to enter external data resources without exposing sensitive statistics. Also combines data integration with machine learning.

Azure 91

Azure Analytics Storage Artificial Inteligence 91

Altexsoft

JUNE 7, 2021

Hadoop and Spark are the two most popular platforms for Big Data processing. They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. Which Big Data tasks does Spark solve most effectively? How does it work?

Big Data 98

Big Data Tools Data Storage 98

TechCrunch

DECEMBER 16, 2020

It stems from us seeing the explosive growth of the data warehouse space, both in terms of technology advancements as well as like accessibility and adoption. […] Our goal is to be seen as the company that makes the warehouse not just for analytics but for these operational use cases.”

Data 251

Data B2C Analytics Big Data 251

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges.

Big Data 63

Big Data Data Storage Microservices 63

Altexsoft

APRIL 22, 2020

So, along with data scientists who create algorithms, there are data engineers, the architects of data platforms. In this article we’ll explain what a data engineer is, the field of their responsibilities, skill sets, and general role description. What is a data engineer?

Data Engineering 69

Data Engineering Engineering Artificial Inteligence Data 69

InfoWorld

FEBRUARY 9, 2024

Microsoft Fabric encompasses data movement, data storage, data engineering, data integration, data science, real-time analytics, and business intelligence, along with data security, governance, and compliance. To read this article in full, please click here

Big Data 78

Big Data Data Azure Google Cloud 78

Gorilla Logic

APRIL 27, 2022

Are you a data engineer or seeking to become one? This is the first entry of a series of articles about skills you’ll need in your everyday life as a data engineer. With SQL, you can also work with complex data types like arrays and JSON objects. This blog post is for you.

Data Engineering 59

Data Engineering Engineering Data Windows 59

CTOvision

JUNE 15, 2015

They also launched a plan to train over a million data scientists and data engineers on Spark. As data and analytics are embedded into the fabric of business and society –from popular apps to the Internet of Things (IoT) –Spark brings essential advances to large-scale data processing. Related articles.

Open Source 117

Open Source Artificial Inteligence Big Data Machine Learning 117

KitelyTech

FEBRUARY 3, 2021

Big data and data science are important parts of a business opportunity. How companies handle big data and data science is changing so they are beginning to rely on the services of specialized companies. User data collection is data about a user who is collected for market research purposes.

Big Data 52

Big Data Data Development Business Intelligence 52

Apiumhub

APRIL 8, 2021

Adrian specializes in mapping the Database Management System (DBMS), Big Data and NoSQL product landscapes and opportunities. Ronald van Loon has been recognized among the top 10 global influencers in Big Data, analytics, IoT, BI, and data science. Ronald van Loon. Marcus Borba. Cindi Howson.

Artificial Inteligence 110

Artificial Inteligence Technical Advisors Data Machine Learning 110

Agile Engine

DECEMBER 27, 2023

From emerging trends to hiring a data consultancy, this article has everything you need to navigate the data analytics landscape in 2024. What is a data analytics consultancy? Big data consulting services 5. 4 types of data analysis 6. Data analytics use cases by industry 7. Key takeaways 2.

Big Data 52

Big Data Analytics Data Analysis 52

Altexsoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Maintained by the Apache Software Foundation, Apache Spark is an open-source, unified engine designed for large-scale data analytics.

Weak Development Team 52

Weak Development Team Big Data Data Artificial Inteligence 52

Altexsoft

FEBRUARY 11, 2023

This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated. Hiring a well-skilled data architect can be very helpful for that purpose. What is a data architect? What is the main difference between a data architect and a data engineer?

Data 87

Data Data Engineering Big Data Architecture 87

InfoQ Culture Methods

SEPTEMBER 6, 2019

Is it all about customer-centric business, or is there any data left? Can we integrate data analytics and customer empathy? This article explores how we can move towards a more customer-centric business and what information we require in order to understand the most valuable thing we have: our customer.

Analytics 66

Analytics Agile Data Big Data 66

Altexsoft

DECEMBER 9, 2020

Moreover, the MicroStrategy Global Analytics Study reports that access to data is extremely limited, taking 60 percent of employees hours or even days to get the information they need. To generalize and describe the basic maturity path of an organization, in this article we will use the model based on the most common one suggested by Gartner.

Analytics 102

Analytics Technical Review Technology Applications 102

Hacker Earth Developers Blog

JUNE 26, 2019

Finding the right candidate for the Data Science role. Finding the right candidate for the role of a Data Scientist can be tricky and challenging. This article will help you understand what Data Science is and what skill sets to look for in a candidate when hiring for a Data Science role. . Data Science.

Data 200

Data How To Artificial Inteligence Machine Learning 200

Altexsoft

JUNE 29, 2021

This article will focus on the role of a machine learning engineer, their skills and responsibilities, and how they contribute to an AI project’s success. The role of a machine learning engineer in the data science team. Who does what in a data science team. Machine learning engineer vs. data scientist.

Artificial Inteligence 105

Artificial Inteligence Machine Learning Engineering Data Engineering 105

CIO

FEBRUARY 14, 2023

A 2023 New Vantage Partners/Wavestone executive survey highlights how being data-driven is not getting any easier as many blue-chip companies still struggle to maximize ROI from their plunge into data and analytics and embrace a real data-driven culture: 19.3% report they have established a data culture 26.5%

Artificial Inteligence 174

Artificial Inteligence Strategy Data Machine Learning 174

CIO

DECEMBER 10, 2024

As a data-driven company, InnoGames GmbH has been exploring the opportunities (but also the legal and ethical issues) that the technology brings with it for some time. Volker Janz has been part of the data team at InnoGames GmbH for over a decade. InnoGames GmbH wants to play an active role in shaping this development.

Games 147

Games Artificial Inteligence Company Artificial Intelligence 147

Strategy Driven

AUGUST 27, 2015

The Internet and cloud computing have revolutionized the nature of data capture and storage, tempting many companies to adopt a new 'Big Data' philosophy: collect all the data you can; all the time. Big Data is Not Just More Data : That’s because the nature of the data we can now collect has changed.

Big Data 33

Big Data Data Storage Journal 33

Kentik

JULY 18, 2016

Seeing Beneath the Surface with Post-Hadoop Big Data. Not long ago, the New York Times published a fascinating article about a rug designer named Luke Irwin who lives in Wiltshire, England. Data-driven insights can boost user satisfaction, make a business more competitive, and increase profits. Dig deep without a backhoe.

Big Data 40

Big Data Network Analytics Data 40

Altexsoft

MARCH 30, 2023

Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. In this article, we’ll highlight the reasoning behind this choice and the challenges related to it. How data engineering works in 14 minutes.

Weak Development Team 64

Weak Development Team Artificial Inteligence Machine Learning Software Review 64

Altexsoft

APRIL 16, 2021

However, when it comes to analyzing large volumes of data from different angles, the logic of OLTP has serious limitations. So, we need a solution that’s capable of representing data from multiple dimensions. In this article, we’ll talk about such a solution —- Online Analytical Processing , or OLAP technology. Building a cube.

Analytics 98

Analytics Analysis Storage Business Intelligence 98

Altexsoft

JANUARY 22, 2020

Please note: this topic requires some general understanding of analytics and data engineering, so we suggest you read the following articles if you’re new to the topic: Data engineering overview. Data visualization as a part of data representation and analytics.

Analytics 20

Analytics Data IoT Analysis 20

Confluent

FEBRUARY 6, 2019

This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Impedance mismatch between data scientists, data engineers and production engineers. For now, we’ll focus on Kafka.

Artificial Inteligence 107

Artificial Inteligence Machine Learning Scalability Data Engineering 107

Dzone - DevOps

FEBRUARY 16, 2023

However, in today's era, what's more, important than the data itself is the ability to locate your wanted information among all the overflowing data quickly. So in this article, I will talk about how I improved overall data processing efficiency by optimizing the choice and usage of data warehouses.

Data 87

Data Storage ChatGPT Architecture 87

Cloudera

FEBRUARY 22, 2021

It builds on a foundation of technologies from CDH (Cloudera Data Hub) and HDP (Hortonworks Data Platform) technologies and delivers a holistic, integrated data platform from Edge to AI helping clients to accelerate complex data pipelines and democratize data assets. query failures, cost overruns).

Data 82

Data Analytics Government Technical Review 82

Altexsoft

AUGUST 21, 2019

Data obsession is all the rage today, as all businesses struggle to get data. But, unlike oil, data itself costs nothing, unless you can make sense of it. Dedicated fields of knowledge like data engineering and data science became the gold miners bringing new methods to collect, process, and store data.

Development 44

Development Software Engineering Data Engineering Architecture 44

CTOvision

MARCH 1, 2016

Related articles. SanDisk: Senior Big Data Engineer/Hadoop Developer (kdnuggets.com). Find more information on Hortonworks ' announcements here. Watch Hortonworks ' Announcement Event here. Apache Hadoop Wordcount Example (examples.javacodegeeks.com).

Analytics 61

Analytics Strategy Big Data Data Engineering 61

Confluent

FEBRUARY 28, 2019

For details on the format and internals, please see our previous article or the documentation for the Neo4j sink. We are also working with several collaborators on a few article series on how to use our Kafka integration in practice. You control ingestion by defining Cypher statements per topic that you want to ingest. Stay tuned.

Open Source 88

Open Source Testing Data System 88

Altexsoft

JULY 23, 2020

This article. It facilitates collaboration between a data science team and IT professionals, and thus combines skills, techniques, and tools used in data engineering, machine learning, and DevOps — a predecessor of MLOps in the world of software development. Data validation. Data preparation.

Artificial Inteligence 145

Artificial Inteligence Machine Learning DevOps Tools 145

Altexsoft

FEBRUARY 10, 2021

Unless you meet it in the article saying that “only 13 percent data science projects make it into production.” This sounds really ominous — especially, for companies heavily investing in data-driven transformations. New approaches arise to speed up the transformation of raw data into useful insights.

Analytics 75

Analytics DevOps Development Software Review 75

Hu's Place - HitachiVantara

JANUARY 3, 2019

” Deployments of large data hubs have only resulted in more data silos that are not easily understood, related, or shared. In order to utilize the wealth of data that they already have, companies will be looking for solutions that will give comprehensive access to data from many sources.

Trends 86

Trends Artificial Inteligence Machine Learning Data Center 86

Cloudera

MAY 18, 2021

Finally, IaaS deployments required substantial manual effort for configuration and ongoing management that, in a way, accentuated the complexities that clients faced deploying legacy Hadoop implementations in the data center. Experience configuration / use case deployment: At the data lifecycle experience level (e.g.,

Cloud 86

Cloud Technical Review Storage Backup 86

Hu's Place - HitachiVantara

SEPTEMBER 26, 2018

Malcolm’s books and articles often provide unexpected insights which helps us understand the events around us and enable us to make better decisions. While Malcolm is known for his best sellers, there are a lot of ideas that are created in his New Yorker articles that are creating even more interest today.

Software Review 60

Software Review Systems Review Technical Review Big Data 60

Altexsoft

JANUARY 14, 2021

Though there are countless options for storing, analyzing, and indexing data, data warehouses have remained to the point. When reviewing BI tools , we described several data warehouse tools. In this article, we’ll take a closer look at the top cloud warehouse software, including Snowflake, BigQuery, and Redshift.

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Backup Azure Software Review Architecture 115