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.

Data 327

Data Database Administration Data Engineering Artificial Inteligence 327

Mobilunity

AUGUST 3, 2021

The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer? Big Data requires a unique engineering approach. Big Data Engineer vs Data Scientist.

Big Data 52

Big Data Data Engineering Engineering Data 52

CIO

JUNE 23, 2023

Not only should the data strategy be cognizant of what’s in the IT and business strategies, it should also be embedded within those strategies as well, helping them unlock even more business value for the organization.

Strategy 278

Strategy Technical Review Data Software Review 278

TechCrunch

NOVEMBER 18, 2021

There are three core roles involved in ML modeling, but each one has different motivations and incentives: Data engineers: Trained engineers excel at gleaning data from multiple sources, cleaning it and storing it in the right formats so that analysis can be performed.

Enterprise 344

Enterprise Artificial Inteligence Data Engineering Data Center 344

Cloudera

AUGUST 20, 2020

Data from the US Treasury website show which companies received PPP loans and how many jobs were retained. Analysis of this data presents three challenges. First, the size of the data is significant. The amount of time to pull, curate, transform, retrieve and report on that data is time intensive. Objective.

Data Engineering 64

Data Engineering Engineering Programming Data 64

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

CIO

JUNE 7, 2022

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 analysts use a number of methods and techniques to analyze data.

Analytics 332

Analytics Data Analysis Business Analytics 332

CIO

JUNE 14, 2023

Candidates are required to complete a minimum of 12 credits, including four required courses: Algorithms for Data Science, Probability and Statistics for Data Science, Machine Learning for Data Science, and Exploratory Data Analysis and Visualization. Candidates have 90 minutes to complete the exam.

Big Data 316

Big Data Analytics Data eLearning 316

TechCrunch

OCTOBER 13, 2022

Data engineers have a big problem. Almost every team in their business needs access to analytics and other information that can be gleaned from their data warehouses, but only a few have technical backgrounds. The New York-based startup announced today that it has raised $7.6

Operating System 233

Operating System Technical Review Analytics Systems Review 233

CIO

JANUARY 17, 2023

It shows in his reluctance to run his own servers but it’s perhaps most obvious in his attitude to data engineering, where he’s nearing the end of a five-year journey to automate or outsource much of the mundane maintenance work and focus internal resources on data analysis. It’s not a good use of our time either.”

Data Engineering 287

Data Engineering Engineering Data CTO Coach 287

Dataiku

DECEMBER 7, 2023

Full disclosure: As a citizen data scientist, I’ve never formally trained as a software developer or professional data engineer.

Data 82

Data Machine Learning Artificial Inteligence Data Engineering 82

CIO

DECEMBER 16, 2022

Other non-certified skills attracting a pay premium of 19% included data engineering , the Zachman Framework , Azure Key Vault and site reliability engineering (SRE). Close behind and rising fast, though, were security auditing and bioinformatics, offering a pay premium of 19%, up 18.8% since March.

Technical Review 232

Technical Review Analytics AWS SCRUM 232

O'Reilly Media - Data

APRIL 11, 2018

It’s important to understand the differences between a data engineer and a data scientist. Misunderstanding or not knowing these differences are making teams fail or underperform with big data. I think some of these misconceptions come from the diagrams that are used to describe data scientists and data engineers.

Data Engineering 280

Data Engineering Engineering Data Artificial Inteligence 280

CIO

SEPTEMBER 29, 2023

These skills include expertise in areas such as text preprocessing, tokenization, topic modeling, stop word removal, text classification, keyword extraction, speech tagging, sentiment analysis, text generation, emotion analysis, language modeling, and much more.

Generative AI 357

Generative AI ChatGPT Machine Learning Artificial Inteligence 357

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 consists of 60 questions and the candidate has 90 minutes to complete it.

Artificial Inteligence 317

Artificial Inteligence Data Machine Learning Azure 317

TechCrunch

MAY 26, 2022

He’s the founder of Manta , a data lineage platform that automatically scans an organization’s data sources to build a map of data flows. “Data-driven decisions can only be as good as the quality of the underlying data sets and analysis.

Data 228

Data Weak Development Team Enterprise Analysis 228

TechCrunch

SEPTEMBER 29, 2022

Petrossian met Coalesce’s other co-founder, Satish Jayanthi, at WhereScape, where the two were responsible for solving data warehouse problems for large organizations. (In In computing, a “data warehouse” refers to systems used for reporting and data analysis — analysis usually germane to business intelligence.)

Enterprise 184

Enterprise Data Business Intelligence Analytics 184

Dzone - DevOps

FEBRUARY 7, 2023

As digital transformation reaches more industries, the number of data points generated is growing exponentially. As such, data integration strategies to collect such large volumes of data from different sources in varying formats and structures are now a primary concern for data engineering teams.

Strategy 95

Strategy Data Data Engineering Analysis 95

CIO

NOVEMBER 9, 2022

Natural language presentation makes It easier to know what to look for in an analysis. It also removes the inconsistency in the way data is interpretated by spelling out exactly what should be taken away from the analysis.” Users have freedom to slice and dice the data without technical know-how,” he says.

Analytics 341

Analytics Metrics Government Business Intelligence 341

Altexsoft

FEBRUARY 11, 2023

Data architect and other data science roles compared Data architect vs data engineer Data engineer is an IT specialist that develops, tests, and maintains data pipelines to bring together data from various sources and make it available for data scientists and other specialists.

Data 87

Data Data Engineering Big Data Architecture 87

Cloudera

JUNE 26, 2023

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. For data engineering and data science teams, CDSW is highly effective as a comprehensive platform that trains, develops, and deploys machine learning models.

Tools 76

Tools Data Engineering Analytics Testing 76

TechCrunch

SEPTEMBER 1, 2022

Akmal started Falkon in 2020 alongside Josh Zana and Aakash Kambuj as an “augmented analytics” company with the goal of improving business operations through analysis and automation. They’d all three worked together on the OneDrive team at Microsoft and went on to spend time at Dropbox, Amazon, Amperity, Code.org and Zulily.

Weak Development Team 223

Weak Development Team Analytics Marketing Business Intelligence 223

CIO

JANUARY 16, 2024

Still, to ensure workers gain the most out of the tools, Mayar suggested multimodal LLMs combining structured datasets and unstructured data should be designed smaller and for specific tasks. Gen AI is not a magic bullet,” she said at the summit. But he still does not see LLMs replacing human cognition any time soon.

Generative AI 297

Generative AI Technical Advisors Artificial Inteligence CTO Coach 297

TechCrunch

JANUARY 10, 2023

Metaplane also attempts to establish lineage from data in a data warehouse — the systems used for reporting and data analysis — and notify stakeholders of issues via their tool of choice (e.g. “Metaplane is the Datadog for Data,” he added. Slack, PagerDuty, email).

Data 241

Data Software Review Technical Review Systems Review 241

Kentik

APRIL 12, 2023

DataOps is a methodology that aims to streamline and automate managing and delivering data throughout its lifecycle, from ingestion to analysis and visualization. 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.

Network 52

Network Data Engineering Machine Learning Artificial Inteligence 52

Data Virtualization

DECEMBER 23, 2021

Reading Time: 5 minutes As I embark on my new journey with Denodo and data virtualization, I am now frequently asked, “What is data virtualization?” Unless I am talking to a data engineer or a data architect (this would help explain it, if you.

Virtualization 52

Virtualization Data Data Engineering Analysis 52

Data Virtualization

DECEMBER 23, 2021

Reading Time: 5 minutes As I embark on my new journey with Denodo and data virtualization, I am now frequently asked, “What is data virtualization?” Unless I am talking to a data engineer or a data architect (this would help explain it, if you.

Virtualization 52

Virtualization Data Data Engineering Analysis 52

Mentormate

NOVEMBER 29, 2022

Simply put, actionable insights are the result of being a data-driven organization. They are the conclusion of successful data management and analysis that empowers decision-making and planning. Insights are the filtered stream flowing from the pooled data and information. What are Actionable Insights?

Analytics 98

Analytics Analysis Business Intelligence Data 98

CIO

JUNE 22, 2023

There’s a demand for skills such as cybersecurity, cloud, IT project management, UX/UI design, change management, and business analysis. There’s a high demand for software engineers, data engineers, business analysts and data scientists, as finance companies move to build in-house tools and services for customers.

Industry 302

Industry UI/UX Telecommunications Quality Assurance 302

CIO

JULY 6, 2023

In contrast, Oracle is yet to configure how it will help enterprises access data and model tuning tools as part of its planned service. The suggestions feature, on the other hand, is expected to provide recommendations across various tasks, such as providing survey questions.

Generative AI 240

Generative AI Artificial Inteligence Strategy Google Cloud 240

Netflix Tech

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.

Data 90

Data Analysis Data Engineering Comparison 90

Kentik

FEBRUARY 27, 2023

It means seeing trends and patterns from a macro level, but it also means getting very granular to pursue any line of analysis of your data. Still, it will be useless if it takes forever to do anything meaningful with that data. Speed and efficiency were the main drivers in its development from the start.

Network 98

Network Data WAN Metrics 98

CTOvision

JULY 25, 2015

Adatao was founded by a team of highly regarded big data engineers and machine learning masters to build a unified solution for data analysis. Adatao supports both business users and the famous dream unicorn data scientist, all on one unified solution.

Data 109

Data Machine Learning Artificial Inteligence Big Data 109

CIO

JUNE 28, 2023

The R&D laboratories produced large volumes of unstructured data, which were stored in various formats, making it difficult to access and trace. That, in turn, led to a slew of manual processes to make descriptive analysis of the test results.

Technical Review 232

Technical Review Analytics Innovation Artificial Intelligence 232

Cloudera

JULY 18, 2023

But let’s face it, navigating the world of any SQL engine is a daunting task, and Hive is no exception. As a Hive user, you will find yourself wanting to go beyond surface-level analysis, and deep dive into the intricacies of how a Hive query is executed. Conversely, you must know if there are any underutilized pools.

Systems Review 73

Systems Review Metrics Trends Performance 73

O'Reilly Media - Ideas

JANUARY 8, 2019

The demand for data skills (“the sexiest job of the 21st century”) hasn’t dissipated. LinkedIn recently found that demand for data scientists in the US is “off the charts,” and our survey indicated that the demand for data scientists and data engineers is strong not just in the US but globally.

Trends 86

Trends Data Machine Learning Artificial Inteligence 86

TechCrunch

MAY 18, 2022

Labeling data like legal contracts, medical images, and scientific literature requires domain expertise that not just any annotator has. In an MIT analysis of popular AI data sets, researchers found mislabeled data like one breed of dog confused for another and an Ariana Grande high note categorized as a whistle.

Open Source 203

Open Source Weak Development Team Artificial Inteligence Data 203