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

The Crazy Programmer

NOVEMBER 6, 2021

Currently, the demand for data scientists has increased 344% compared to 2013. hence, if you want to interpret and analyze big data using a fundamental understanding of machine learning and data structure. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering.

Artificial Inteligence 290

Artificial Inteligence Blockchain Artificial Intelligence Software Review 290

Altexsoft

JULY 29, 2022

What does it take to store all New York Times articles published between 1855 and 1922? Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Source: The Wall Street Journal.

Big Data 59

Big Data Data Google Cloud Storage 59

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

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

Toptal

DECEMBER 6, 2016

With the rise of big data and data science, storage and retrieval have become a critical pipeline component for data use and analysis. Recently, new data storage technologies have emerged. Which one is best suited for data engineering? But the question is: Which one should you choose?

Data Engineering 85

Data Engineering Storage Engineering Data 85

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

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

O'Reilly Media - Ideas

FEBRUARY 11, 2019

Many companies are just beginning to address the interplay between their suite of AI, big data, and cloud technologies. I’ll also highlight some interesting uses cases and applications of data, analytics, and machine learning. Foundational data technologies. Data Platforms. Data Integration and Data Pipelines.

Big Data 87

Big Data Technology Tools Cloud 87

TechCrunch

JANUARY 26, 2022

Israeli startup Firebolt has been taking on Google’s BigQuery, Snowflake and others with a cloud data warehouse solution that it claims can run analytics on large datasets cheaper and faster than its competitors. Another sign of its growth is a big hire that the company is making. billion valuation.

Analytics 218

Analytics Data Big Data Business Intelligence 218

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

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 Machine Learning Artificial Inteligence Software Review 64

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

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 65

Analytics Agile Data Big Data 65

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 109

Artificial Inteligence Technical Advisors Data Machine Learning 109

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

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 256

Artificial Inteligence Strategy Data Machine Learning 256

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

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

Kentik

MARCH 7, 2023

Solving these problems for distributed cloud networks has required a big data approach, ultimately resulting in the evolution of network observability. Rich context and real-time datasets allow network engineers to dynamically filter, drill down, and map networks as queries adjust. Leverage automated insights and response flows.

Network 99

Network Cloud Data Case Study 99

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 71

Data ChatGPT Storage Architecture 71

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 Big Data Machine Learning Artificial Inteligence 117

Netflix Tech

JULY 21, 2022

Problem Statement The purpose of this article is to give insights into analyzing and predicting “out of memory” or OOM kills on the Netflix App. We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform.

Machine Learning 71

Machine Learning Artificial Inteligence Systems Review Big Data 71

Altexsoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Machine Learning 52

Machine Learning Artificial Inteligence Data Systems Review 52

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 79

Data Analytics Government Technical Review 79

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

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

Cloudera

MARCH 22, 2022

The intent of this two-part article series is to articulate the value proposition of Cloudera Data Platform (CDP) as an inorganic growth enabler in different M&A settings such as corporate carve-outs, mergers and acquisitions. data engineering, data warehousing etc.);

Technical Review 80

Technical Review Strategy Data Analytics 80

Altexsoft

NOVEMBER 7, 2022

You can hardly compare data engineering toil with something as easy as breathing or as fast as the wind. The platform went live in 2015 at Airbnb, the biggest home-sharing and vacation rental site, as an orchestrator for increasingly complex data pipelines. How data engineering works. What is Apache Airflow?

Weak Development Team 52

Weak Development Team Technical Review Software Review Systems Review 52

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 85

Cloud Technical Review Storage Backup 85

Altexsoft

OCTOBER 21, 2022

Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. In this article, we’ll explain why businesses choose Kafka and what problems they face when using it. Cloudera , focusing on Big Data analytics. What is Kafka?

Weak Development Team 93

Weak Development Team Technical Review Systems Review Software Review 93

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

Exadel

AUGUST 26, 2020

So, to know what data is available and in what structure it is organized simplifies the overall business processes and makes it possible to see the whole picture in a clear and transparent way. For example, a company may have millions of lines of data in its database, but business leaders need a summary report for just the previous month.

Analytics 52

Analytics Data How To Machine Learning 52

Abhishek Tiwari

JULY 7, 2023

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

Data 52

Data Transportation Scalability Systems Review 52

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

Mobilunity

NOVEMBER 24, 2021

The demand for specialists who know how to process and structure data is growing exponentially. In most digital spheres, especially in fintech, where all business processes are tied to data processing, a good big data engineer is worth their weight in gold. Who Is an ETL Engineer?

Development 52

Development Storage Recruiting Architecture 52