Big Data Architecture in Data Processing and Data Access by Stephanie Shen via @DataScienceCtrl

Over the past 20+ years, it has been amazing to see how IT has been evolving to handle the ever-growing amount of data, via technologies including relational OLTP (Online Transactional Processing) database, data warehouse, ETL (Extraction, Transformation and Loading) and OLAP (Online Analytical Processing) reporting, big data and now AI, Cloud and IoT.

This was very clear and insightful. Worth a read as I think it could clear up a few misunderstandings.

SQL vs NoSQL: 7 Key Takeaways by Alex Williams via @kdnuggets

People assume that NoSQL is a counterpart to SQL. Instead, it’s a different type of database designed for use-cases where SQL is not ideal. The differences between the two are many, although some are so crucial that they define both databases at their cores.

I enjoyed reading this thoughtful article. I think it helps to clear up some potential confusion and ensures that you really understand via his careful use of diagrams.

Do You Know Python Has A Built-In Database? by Christopher Tao via @TDataScience

An introduction of the Python built-in library - sqlite3.

This is very useful and something that I never really understood until I read this.  Includes some code examples and a link to the documentation.

7 Steps to Mastering SQL for Data Science — 2019 Edition: by Matthew Mayo via @kdnuggets

Follow these updated 7 steps to go from SQL data science newbie to practitioner in a hurry. We consider only the necessary concepts and skills and provide quality resources for each.

Something that everyone who writes code against a data source needs to understand (but it is especially important for SQL code).  Contains a great visual and links to further information.

WEBINAR: Columnar Databases: Best Choice for Real-Time Analytics - 19th September 2018

Business today often calls for analyzing millions or even billions of rows of data  on demand and in real time. And although relational databases are unmatched  for transactional workloads, columnar databases allow for faster and easier analytical queries. In this latest Data Science Central webinar, we'll explore how columnar databases can: Decrease the need to read from disk Massively compress your dataset Eliminate the need for indexes Support ad hoc, on-demand queries at any scale We'll use MariaDB AX, an open source columnar database for enterprises, to demonstrate  how column-based storage can make your analytics more efficient, flexible and scalable –  without sacrificing standard SQL. Speaker: Shane Johnson, Senior Director of Product Marketing -- MariaDB Hosted by: Bill Vorhies, Editorial Director -- Data Science Central Title:  Columnar Databases: Best Choice for Real-Time Analytics Date:  Wednesday, September 19th, 2018 Time:  9:00 AM - 10:00 AM PDT

Register here

Presto for Data Scientists – SQL on anything by Kamil Bajda-Pawlikowski via @kdnuggets

Presto enables data scientists to run interactive SQL across multiple data sources. This open source engine supports querying anything, anywhere, and at large scale.

I have to agree with Kamil - download a free version of it and try it - I think you will be pleasantly surprised.

Developing a successful data governance strategy by Federico Castanedo via @OReillyMedia

Multi-model database architectures provide a flexible data governance platform.

Great article by Federico that is worth reading. There is a free e-book you can download too.

Database skills fetching top pay, study says by David Weldon via @infomgmt

Professionals with the right skillsets are earning the highest pay premiums according to new research from Foote Associates.

Worth reading this so you know the kinds of skills to develop going forward.

WEBINAR: Optimal Data Analytics Architecture - 24 January 2017

Overview

Title: Optimal Data Analytics Architecture

Date: Tuesday, January 24, 2017

Time: 09:00 AM Pacific Standard Time

Duration: 1 hour

Summary

Optimal Data Analytics Architecture

An explosion of Big Data is rapidly changing the IT landscape. While Big Data generates vast opportunities for new sources of revenue, customer insights and operational efficiencies, it also creates new challenges for existing data infrastructure. To keep up with this explosion and capitalise on new data-driven business opportunities, enterprises must select a data analytics architecture that fits the specific needs of their business and the structure of their data. 

Join us for our latest Data Science Central Webinar with guest speakers Mike Gualtieri, VP and Principal Analyst at Forrester, and Steve Sarsfield, product evangelist and spokesperson for HPE Vertica, while they discuss a newly commissioned study on enterprises that select the correct mix of analytical engines and the best database for each job.  They will review:

• How a diversity of analytical engines can drive greater ROI
• Which databases have distinct capabilities and “sweet spots”
• Why no one database can do it all 

Speakers:

Mike Gualtieri --VP Principal Analyst -- Forrester  
Steve Sarsfield -- Product Evangelist and Spokesperson -- HPE Vertica   

Hosted by: 

Bill Vorhies, Editorial Director -- Data Science Central

Register here

WEBINAR: Advanced analytics in the era of big data - 15 December 2016

Complimentary Web Seminar
December 15, 2016
2 PM ET/11 AM PT
Hosted by Information Management

Today’s advanced analytic environments are putting greater pressure on decision support infrastructures, creating a mandate for a better, more agile foundation to support them. If you are cracking under the pressure of delivering BI and analytics in a timely way, register for this webinar to hear experts share tips on delivering value to the business faster.

Learn about cutting-edge, data integration and database technologies that simplify the preparation and engineering of data – automating the means by which it is integrated, transformed, and managed – along with the process of manipulating and analyzing data at massive scale.

Topics to be covered include:

• Technologies that enable the rapid and agile integration and processing of data
• How to simplify and accelerate the efforts of data scientists and business analysts
• The role of big data in advanced analytics

Featured Presenters:

Moderator: Eric Kavanagh Information Management	Speaker: Donald Farmer TreeHive Strategy	Speaker: Shawn Rogers Statistica	Speaker: Imad Birouty Teradata	Speaker: Michael Whitehead WhereScape

Sponsor Content From:

Register here

Three blockchain articles by @VanRijmenam from @Datafloq

In this series of posts, he is providing insights in a technology that will change our world. Blockchain has been said to be as important invention as the Internet and Johann Palychata, a research analyst from BNP Baripas, called Blockchain an invention like the steam or combustion engine.

In part 1 of this series he gave an introduction to Blockchain, in part 2 he provided insights in different types of Blockchain and consensus algorithms and in part 3 he will discuss some of the major challenges we will need to overcome to make Blockchain truly change our world for the better.

This is definitely a must read as this is clearly going to be the future,

SLIDESHOW: What the Top 14 Relational Database Skills Pay via @infomgmt

By most accounts, the demand for professionals with data skills will remain strong heading into 2017. That translates into attractive salaries, especially for those with the most niche skills. According to the just-published “2016 Data Science Salary Survey” by O’Reilly Media, data pros with relational database skills can expect the following pay.

Interesting.

How Campaigns and Companies Use Data to Win the Race by Amir Orad via @Data_Informed

Sisense CEO Amir Orad discusses how political campaigns are leveraging data analytics to target individual voters and guide their advertising spend, how campaigns’ data challenges mirror those of enterprises, and how the analytics efforts of current candidates compare.

Definitely food for thought.

The Emerging Data Design: Bitemporal Data by Mike Lapenna via @infomgmt

With Microsoft joining the club, we now have Oracle, IBM (DB2), Teradata and Microsoft supporting some portion or all of the bitemporal design.

Good to see it become more mainstream - I've been adding the field to support this in data warehouses for years, but to use it properly is clunky so more support for this has got to be a good thing.

7 Steps to Understanding NoSQL Databases by Matthew Mayo via @kdnuggets

Are you a newcomer to NoSQL, interested in gaining a real understanding of the technologies and architectures it includes? This post is for you.

This is incredibly useful and a great overview.  Recommended.

Why Uber Engineering Switched from Postgres to MySQL by Evan Klitzke via @UberEng

Uber Engineering explains the technical reasoning behind its switch in database technologies, from Postgres to MySQL.

I loved this explanation and the level of detail behind it.

Value of Geospatial Data Applications Extends Beyond IoT by Ali Hodroj via @Data_Informed

Location data holds valuable insights for many business verticals beyond the province of the expanding Internet of Things, writes Ali Hodroj of GigaSpaces.

I can see there are many uses and interesting analytics that can be done using this data.

SLIDESHOW: Big Data Skills and Pay Trends That Have Top Impact by David Weldon via @infomgmt

Big data skills continue to be among the most rewarding investments for technologists, and most expensive to pay for to IT leaders, according to the newly released “IT Skills and Certifications Pay Index” by Foote Partners. Here are the skills and certification trends that will most impact you.

Maybe this can help you to know the skills and certifications to concentrate on.

How to Capitalise on the Data Landscape of Tomorrow via @Data_Informed

How to Capitalise on the Data Landscape of Tomorrow by Marshall Daly @Data_Informed - Tableau’s Marshall Daly examines where organisations are storing their data, choices and innovations based on today’s business demands that are shaping the data landscape of tomorrow, and how organisations can build a data workflow to keep pace with that innovation.

Interesting.

Data Blending Is Top-of-Mind at Strata & Hadoop Event via @infomgmt

Data Blending Is Top-of-Mind at Strata & Hadoop Event by David Weldon via +Information Management -  Companies want to blend an array of data for analytics, whether from relational databases, large swaths of machine data or data already living in Hadoop, says Pentaho's Ben Hopkins.

Interesting and worth a read.