How To Build A Database Using Python - Sep 28, 2021.
Implement your database without handling the SQL using the Flask-SQLAlchemy library.
Databases, Flask, Python, SQL
- Stack Overflow Survey Data Science Highlights - Aug 20, 2021.
The results of the 2021 Stack Overflow Developer Survey were recently released, which is a fascinating snapshot of today's developers and the tools they are using. Have a look at some selections from the report, particularly those which may be of interest to data professionals.
Cloud, Data Science, Databases, Developers, Programming, Programming Languages, StackOverflow, Survey
- The NoSQL Know-It-All Compendium - May 13, 2021.
Are you a NoSQL beginner, but want to become a NoSQL Know-It-All? Well, this is the place for you. Get up to speed on NoSQL technologies from a beginner's point of view, with this collection of related progressive posts on the subject. NoSQL? No problem!
Beginners, Databases, NoSQL, SQL
- Document Databases, Explained - Mar 9, 2021.
Out of all the NoSQL database types, document-stores are considered the most sophisticated ones. They store data in a JSON format which as opposed to a classic rows and columns structure.
Beginners, Databases, NoSQL
- Graph Databases, Explained - Feb 26, 2021.
Between the four main NoSQL database types, graph databases are widely appreciated for their application in handling large sets of unstructured data coming from various sources. Let’s talk about how graph databases work and what are their practical uses.
Beginners, Databases, Graph Databases, NoSQL
- Column-Oriented Databases, Explained - Feb 12, 2021.
NoSQL Databases have four distinct types. Key-value stores, document-stores, graph databases, and column-oriented databases. In this article, we’ll explore column-oriented databases, also known simply as “NoSQL columns”.
Beginners, Databases, NoSQL, Programming
- Feature Store vs Data Warehouse - Dec 22, 2020.
A feature store is a data warehouse of features for machine learning. Differently from a data warehouse, it is dual-database: one serving features at low latency to online applications and another storing large volumes of features. Learn how Data Scientists leverage this capability in production-deployed models.
Data Warehouse, Databases, Feature Store, Pipeline
Learning SQL the Hard Way - Jan 8, 2020.
Simply put: This post is about installing SQL, explaining SQL and running SQL.
Databases, MySQL, Programming, SQL
- Why physical storage of your database tables might matter - May 31, 2019.
Follow this investigation into why physical storage of your database tables might matter, from problem identification to possible issue resolutions.
Apache Spark, Databases, Postgres, SQL
- Aspiring Researchers, Engineers, and Entrepreneurs interested in data: This Book is for You - Feb 1, 2019.
Making Databases Work is a collection of chapters written by leading database researcher and enterpreneur Michael Stonebraker and 38 of his collaborators: world-leading database researchers, world-class systems engineers, and business partners.
Advice, Databases, Michael Brodie, Michael Stonebraker
- YouTube videos on database management, SQL, Datawarehousing, Business Intelligence, OLAP, Big Data, NoSQL databases, data quality, data governance and Analytics – free - May 18, 2018.
Watch over 20 hours of YouTube videos on databases and database design, Physical Data Storage, Transaction Management and Database Access, and Data Warehousing, Data Governance and (Big) Data Analytics - all free.
Analytics, Bart Baesens, Big Data, Business Intelligence, Data Governance, Data Quality, Data Warehousing, Databases, NoSQL, SQL, Youtube
- To SQL or not To SQL: that is the question! - May 7, 2018.
This article looks at the emergence of the NoSQL movement and compares it to a traditional relational database.
Databases, NoSQL, Relational Databases, Scalability, SQL
- Graph Databases Burst into the Mainstream - Feb 19, 2018.
What do Amazon, Facebook, Google, IBM, Microsoft and Twitter have in common? They're all adopters of graph databases - a hot technology that continues to evolve.
Databases, Graph Databases, TigerGraph
- Database Bootcamp Webinar Series, Dec 5, 7, 12, 14 - Dec 1, 2017.
The need to be broadly knowledgeable and rapidly understand the existing database ecosystem is growing. Looker broken down and simplified the differentiators of the main database technologies into this series of four, 45-minute webinar sessions.
Databases, Looker, MPP Database, SQL
- How To Write Better SQL Queries: The Definitive Guide – Part 2 - Aug 24, 2017.
Most forget that SQL isn’t just about writing queries, which is just the first step down the road. Ensuring that queries are performant or that they fit the context that you’re working in is a whole other thing. This SQL tutorial will provide you with a small peek at some steps that you can go through to evaluate your query.
Pages: 1 2
Algorithms, Complexity, Databases, Relational Databases, SQL
- How To Write Better SQL Queries: The Definitive Guide – Part 1 - Aug 23, 2017.
Most forget that SQL isn’t just about writing queries, which is just the first step down the road. Ensuring that queries are performant or that they fit the context that you’re working in is a whole other thing. This SQL tutorial will provide you with a small peek at some steps that you can go through to evaluate your query.
Pages: 1 2
Databases, Relational Databases, SQL
- KDnuggets™ News 17:n32, Aug 23: The Rise of GPU Databases; Instagramming with Python for Data Analysis - Aug 23, 2017.
Also: Deep Learning and Neural Networks Primer; A New Beginning to Deep Learning; The most important step in Machine Learning process.
Databases, GPU, Instagram, Python
- How to Make Your Database 200x Faster Without Having to Pay More - Nov 22, 2016.
Waiting long for a BI query to execute? I know it’s annoyingly frustrating… It’s a major bottle neck in day-to-day life of a Data Analyst or BI expert. Let’s learn some of the easy to use solutions and a very good explanation of why to use them, along with other advanced technological solutions.
Pages: 1 2 3
BI, Databases, OLTP, Optimization, Performance, Sampling, SnappyData, SQL
- iSight Cloud – Lightning fast visualizations on large data sets - Nov 22, 2016.
SnappyData is launching a FREE cloud service called iSight-Cloud so anyone can try our engine and provide us some feedback. You can try our simple demos in a visual environment or even bring your own data sets to try.
Apache Zeppelin, Big Data, Data Visualization, Databases, Sampling, SnappyData
- Top KDnuggets tweets, Aug 17-23: Approaching (Almost) Any #MachineLearning Problem; #Database Nirvana – can one query language rule them all? - Aug 24, 2016.
In Search of #Database Nirvana - can one query language rule them all? Google Cloud Datalab: #Jupyter meets #TensorFlow, #cloud meets local deployment; Approaching (Almost) Any #MachineLearning Problem; The Gentlest Introduction to Tensorflow Part 1.
Databases, Jupyter, Machine Learning, TensorFlow, Top tweets
- The Inside Scoop on Apache Sqoop, Aug 25 Webinar - Aug 23, 2016.
Last chance! Register for Aug 25 webinar to learn about the best practices for using Apache Sqoop and interoperability with JDBC data sources from relational to cloud.
Cloud Computing, Databases, Progress Software, Sqoop
- KxCon2016, International kdb+ programmer conference, May 19-22, Montauk, NY - Apr 22, 2016.
Kdb+ time-series database provides high performance analytics on very large-scale datasets. Kdb+ users and coders will gather for KxCon2016, 3 days of presentations and hands-on workshops.
Databases, kdb+, Montauk, NY, Programming Languages, Time Series
- Which Database is best for an Analyst? - Dec 10, 2015.
Database comparisons usually look at architecture, cost, scalability, and speed, but rarely address the other key factor: how hard is writing queries for these databases? We examine which of the top 8 databases are easiest to use.
Pages: 1 2
Amazon Redshift, Apache Hive, BigQuery, Data Analyst, Databases, MySQL, NoSQL, SQL Server, Vertica
- Amazon Top 20 Books in Databases & Big Data - Nov 17, 2015.
These are the most popular database & big data books on Amazon. Some interesting options here, so hopefully you find something useful to your current requirements.
Amazon, Big Data, Databases, Matthew Mayo
- Interview: Dave McCrory, Basho on Distributed Database Needs of a Future Enterprise - Mar 16, 2015.
We discuss the future of distributed storage for enterprise, Scale-up vs. Scale-out, software design patterns in Cloud era, microservices model and the place for legacy database in modern enterprise IT.
Basho, Cloud Computing, Databases, Dave McCrory, Distributed Systems, Integration, Interview, SQL
- Interview: Peter Alvaro, UC Berkeley, on Consistency Challenge in Distributed Systems - Dec 17, 2014.
We discuss the performance limitations caused by treating datastore as black box, consistency as an application-level property, Dedalus and LDFI approach for testing.
Consistency, Data, Databases, Distributed Systems, NoSQL, Peter Alvaro, UC Berkeley
