datapine

AUGUST 29, 2022

Best for : Software engineers looking to learn the fundamentals of designing data-intensive applications, the pros, and cons of the different technologies available, as well as key concepts needed to succeed in the process. An excerpt from a rave review : “This is one of the greatest technical books I have ever read.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Insight

AUGUST 16, 2019

Which are the most important concepts and frameworks one should understand? It starts very basic with introductory articles to Python, but also includes links to courses covering the Hadoop ecosystem, including Spark and Hive. What is Data Engineering and what is the role of a Data Engineer? you are not alone!

Big Data 51

Big Data Data Science Data Processing Machine Learning 51

Smart Data Collective

MAY 20, 2019

Quantitative analysis, experimental analysis, data scaling, automation tools and, of course, general machine learning are all skills that modern data analysts should seek to hone. With databases, for example, choices may include NoSQL, HBase and MongoDB but its likely priorities may shift over time.

Analytics 111

Analytics Machine Learning Business Intelligence Big Data 111

Domino Data Lab

FEBRUARY 4, 2019

Of course!!” Of course, some questions in business cannot be answered with historical data. Perhaps the company wanted to introduce more advanced techniques by the 2010s, so they added a data science team because their BI people were reluctant to upskill into NoSQL tools, machine learning, etc. Yeah, not so much.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

Jet Global

MAY 1, 2023

Once they build a proof of concept with your very own data, you can use it to validate your direction with your customers. In some cases, such as when building a proof-of-concept for a newly envisioned application, this approach can be a good starting point. Finish a proof-of-concept? Make my final decision? Start development?

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

O'Reilly on Data

FEBRUARY 18, 2020

Starting with data engineering, the backbone of all data work (the category includes titles covering data management, i.e., relational databases, Spark, Hadoop, SQL, NoSQL, etc.). Interest in cloud-related concepts and terms continues to increase on O’Reilly online learning, albeit at a slower rate. This follows a 3% drop in 2018.

Data-driven 335

Data-driven Software Statistics Marketing 335

CIO Business Intelligence

JANUARY 20, 2023

It might be in a NoSQL database, a graph database, or in all these other types of databases now available, and making those consistent becomes really challenging,” Orlandini says. Of course, cost is a big consideration, says Orlandini, as well as deciding where to host the data, and having it available in a fiscally responsible way.

Data Lake 127

Data Lake Data-driven Finance Data Architecture 127