Altexsoft

JUNE 25, 2019

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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CIO

OCTOBER 13, 2023

Big data architect: The big data architect designs and implements data architectures supporting the storage, processing, and analysis of large volumes of data. Data architect vs. data engineer The data architect and data engineer roles are closely related.

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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?

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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. So let’s begin with the first and, in my opinion, the most useful tool in your technical tool belt, SQL. This blog post is for you.

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Altexsoft

AUGUST 25, 2020

Big data is tons of mixed, unstructured information that keeps piling up at high speed. That’s why traditional data transportation methods can’t efficiently manage the big data flow. Big data fosters the development of new tools for transporting, storing, and analyzing vast amounts of unstructured data.

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Trigent

JUNE 20, 2022

To do this, they are constantly looking to partner with experts who can guide them on what to do with that data. This is where data engineering services providers come into play. Data engineering consulting is an inclusive term that encompasses multiple processes and business functions.

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Mobilunity

AUGUST 3, 2021

Big Data is a collection of data that is large in volume but still growing exponentially over time. It is so large in size and complexity that no traditional data management tools can store or manage it effectively. Who is Big Data Engineer? Big Data requires a unique engineering approach.

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Cloudera

JUNE 26, 2023

Over time, using the wrong tool for the job can wreak havoc on environmental health. Here are some tips and tricks of the trade to prevent well-intended yet inappropriate data engineering and data science activities from cluttering or crashing the cluster. So which open source pipeline tool is better, NiFi or Airflow?

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Tools Data Engineering Analytics Testing 75

Erik Bernhardsson

DECEMBER 15, 2020

It's a popular attitude among developers to rant about our tools and how broken things are. I had my first job as a software engineer in 1999, and in the last two decades I've seen software engineering changing in ways that have made us orders of magnitude more productive. The insatiable demand for software.

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Cloudera

SEPTEMBER 2, 2021

The shift to cloud has been accelerating, and with it, a push to modernize data pipelines that fuel key applications. That is why cloud native solutions which take advantage of the capabilities such as disaggregated storage & compute, elasticity, and containerization are more paramount than ever.

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Data Engineering Performance Engineering Data 81

Cloudera

JANUARY 12, 2018

I mentioned in an earlier blog titled, “Staffing your big data team, ” that data engineers are critical to a successful data journey. That said, most companies that are early in their journey lack a dedicated engineering group. Image 1: Data Engineering Skillsets.

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Hu's Place - HitachiVantara

JANUARY 15, 2019

For lack of similar capabilities, some of our competitors began implying that we would no longer be focused on the innovative data infrastructure, storage and compute solutions that were the hallmark of Hitachi Data Systems. A REST API is built directly into our VSP storage controllers.

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The Crazy Programmer

NOVEMBER 6, 2021

A cloud architect has a profound understanding of storage, servers, analytics, and many more. They also use tools like Amazon Web Services and Microsoft Azure. Big Data Engineer. Another highest-paying job skill in the IT sector is big data engineering. AI or Artificial Intelligence Engineer.

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CIO

SEPTEMBER 2, 2022

Software engineers are one of the most sought-after roles in the US finance industry, with Dice citing a 28% growth in job postings from January to May. The most in-demand skills include DevOps, Java, Python, SQL, NoSQL, React, Google Cloud, Microsoft Azure, and AWS tools, among others. Data engineer.

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CIO

AUGUST 31, 2022

Software engineers are one of the most sought-after roles in the US finance industry, with Dice citing a 28% growth in job postings from January to May. The most in-demand skills include DevOps, Java, Python, SQL, NoSQL, React, Google Cloud, Microsoft Azure, and AWS tools, among others. Data engineer.

Software Engineering 246

Software Engineering Data Engineering DevOps AWS 246

CIO

JANUARY 19, 2024

The exam tests general knowledge of the platform and applies to multiple roles, including administrator, developer, data analyst, data engineer, data scientist, and system architect. The exam tests your knowledge of and ability to integrate machine learning into various tools and applications.

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TechCrunch

MAY 24, 2022

Preql founders Gabi Steele and Leah Weiss were data engineers in the early days at WeWork. They later opened their own consultancy to help customers build data stacks, and they saw a stubborn consistency in the types of information their clients needed. That’s really what motivates us.

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CIO

JULY 6, 2023

OCI’s Supercluster includes OCI Compute Bare Metal, which provides an ultralow-latency remote direct access memory (RDMA) over a Converged Ethernet (RoCE) cluster for low-latency networking, and a choice of high-performance computing storage options.

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CIO

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. Data analytics tools.

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Analytics Data Analysis Business Analytics 332

CIO

JUNE 14, 2023

Organization: Cloudera Price: US$330 How to prepare: Cloudera recommends candidates have familiarity with Salesforce, BI tools, Google Sheets, Microsoft Excel, and Python/R. CDP Generalist The Cloudera Data Platform (CDP) Generalist certification verifies proficiency with the Cloudera CDP platform.

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CIO

FEBRUARY 14, 2023

Organizations have balanced competing needs to make more efficient data-driven decisions and to build the technical infrastructure to support that goal. A cloud-native approach with Kubernetes and containers brings scalability and speed with increased reliability to data and AI the same way it does for microservices.

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Altexsoft

SEPTEMBER 9, 2022

We’ll briefly recap the basics first and then discuss metadata management and tools that can come in handy. Metadata is basically information that describes other data. It helps us understand the origin, structure, nature, and context of data. It aims at making data assets understandable and discoverable for users.

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CIO

JUNE 22, 2023

Consulting In the consulting industry, technology has become an important tool for making decisions, designing solutions, improving processes, and providing insights on optimizing business strategy.

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CIO

AUGUST 2, 2023

The layer cake metaphor shifts the data discussion from an IT discussion to the intersection of business strategy and technology. So it’s about how we create layers from the business concept, like advancing discovery, all the way down to a technology solution, like a visualization tool. Does the data live in one or many clouds?

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CIO

FEBRUARY 13, 2023

On-prem infrastructure will grow cold — with the exception of storage, Nardecchia says. Some storage will likely stay on-prem while more is pushed into the public cloud, he says. For example, the hospital wants the ability to look at imaging and pathology data so staff can better diagnose patients faster and quicker, he says.

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Altexsoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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O'Reilly Media - Data

AUGUST 16, 2018

As companies move from machine learning prototypes to products and services, tools and best practices for productionizing and managing models are just starting to emerge. Today’s data science and data engineering teams work with a variety of machine learning libraries, data ingestion, and data storage technologies.

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Machine Learning Artificial Inteligence Data Engineering Compliance 105

Tenable

NOVEMBER 3, 2022

When our data engineering team was enlisted to work on Tenable One, we knew we needed a strong partner. While the story of Tenable One is, first and foremost, a technology story, the analytics baked into the platform would not be possible without the ability to ingest and process a wide variety of data from a suite of point tools. .

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Data AWS Storage Data Engineering 98

Altexsoft

OCTOBER 29, 2020

But before you dive in, we recommend you reviewing our more beginner-friendly articles on data transformation: Complete Guide to Business Intelligence and Analytics: Strategy, Steps, Processes, and Tools. What is Data Engineering: Explaining the Data Pipeline, Data Warehouse, and Data Engineer Role.

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Testing Tools Software Review Technical Review 63

Mobilunity

MAY 8, 2023

Key zones of an Enterprise Data Lake Architecture typically include ingestion zone, storage zone, processing zone, analytics zone, and governance zone. Ingestion zone is where data is collected from various sources and ingested into the data lake. Storage zone is where the raw data is stored in its original format.

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InnovationM

MAY 14, 2023

In this article, I will share practical insights and technologies utilized in building and harnessing the potential of data lakes. Demystifying Data Lakes Data lakes serve as flexible storage repositories, enabling organizations to store raw and diverse data types, breaking away from the constraints of traditional data warehouses.

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Xebia

MAY 16, 2023

Data Engineers were tempted by the pressure of the moment to give up on testing all together. There was no need for generating your own data; just take a percentage of production data. In many cases, these tasks ended up on the shoulders of the Data Engineers themselves. Overly restrictive governance.

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Kentik

APRIL 12, 2023

It is an extension of DevOps principles and practices to data management, enabling organizations to manage and automate data pipelines for quality, accuracy, and reliability. The DataOps ecosystem comprises several components, including people, processes, and tools. How is DataOps different from DevOps?

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

Altexsoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. What is a data lake?

Architecture 52

Architecture Data Storage Machine Learning 52

Altexsoft

JANUARY 14, 2021

Snowflake, Redshift, BigQuery, and Others: Cloud Data Warehouse Tools Compared. From simple mechanisms for holding data like punch cards and paper tapes to real-time data processing systems like Hadoop, data storage systems have come a long way to become what they are now. Cloud data warehouse architecture.

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Altexsoft

APRIL 16, 2021

Optionally, you may study some basic terminology on data engineering or watch our short video on the topic: What is data engineering. What is data pipeline. Online Analytical Processing can be defined as a set of tools and approaches to represent data from multiple dimensions. Data operations in OLAP.

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Hu's Place - HitachiVantara

APRIL 11, 2019

Few Data Management Frameworks are Business Focused Data management has been around since the beginning of IT, and a lot of technology has been focused on big data deployments, governance, best practices, tools, etc. However, large data hubs over the last 25 years (e.g.,

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