There is a useful guide to read which discusses the a structured approach for designing data-centric solutions on Microsoft Azure. The two different approaches are
Traditional RDBMS workloads.
These designs are for online transaction processing (OLTP) and online analytical processing (OLAP).
Big data solutions. This design looks at big data architecture to handle the ingestion, processing, and analysis of data that is too large or complex for traditional database systems.
There is useful pages to read on machine learning at scale and non relational data.
Chaos, complexity, curiosity and database systems. A place where research meets industry
Welcome
Passionately curious about Data, Databases and Systems Complexity. Data is ubiquitous, the database universe is dichotomous (structured and unstructured), expanding and complex. Find my Database Research at SQLToolkit.co.uk . Microsoft Data Platform MVP
"The important thing is not to stop questioning. Curiosity has its own reason for existing" Einstein
"The important thing is not to stop questioning. Curiosity has its own reason for existing" Einstein
Thursday 28 February 2019
Wednesday 27 February 2019
Monday 25 February 2019
Monday 11 February 2019
Data Trends for 2019
I created a survey question on Twitter to look at data trends. I was interested to see whether people felt that improving the quality of their data was more important than AI data ethics. Data quality is heavily influenced by data ingest so I added this as an option, as i felt it is often over looked, but is a foundation stone of good data quality.
A few definitions:
“Data Ethics describe a code of behaviour, specifically what is right and
wrong, encompassing the following: Data Handling:
generation, recording, curation, processing, dissemination, sharing, and use."
“Data Quality (DQ) as stated
in the DAMA International, Data Management
Book of Knowledge "Refers to
both the characteristics associated with and to the processes used to measure
or improve the quality of data.” Data is
considered high quality to
the degree it is fit for the purposes data consumers
want to apply it."
“Data
ingestion is the process of obtaining and importing data for
immediate use or storage in a database. To ingest something is to
"take something in or absorb something." Data can be streamed
in real time or ingested in batches.”
“Data
ingestion tools provide a framework that allows companies to collect,
import, load, transfer, integrate, and process data from a wide range of data
sources.”
The survey question had 267 votes.
In additions to the results above I received a few additional
comments.
- Neither
- The biggest thing in my opinion is just ethics. How is the data collected?
- Also, what is it being used for. What are the impacts of high or low accuracy models.
- Improving quality and ethics seem to me, to be related tasks
- All of the above?
The results are quite interesting with AI Data Ethics and Improving Data
Quality being the trends that the respondents thought were the most important.
Wednesday 6 February 2019
Improved Microsoft Docs
A cool image from http://www.thinksinc.org/ about Microsoft Docs.
I was looking at the Microsoft Docs pages and its new design. I have found it is much easier to navigate which speeds up searching.
At the top of the page there are 3 helpful options
- Download SQL Server
- Get an Azure VM with SQL Server
- Download SQL Server Management Studio
Then the Microsoft SQL
Documentation has 3 categories covering on premises and cloud.
- SQL Server on Windows
- SQL as an Azure Service
- SQL Server on Linux
There are technology areas to drill down further.
Then a further collection of links to enable a deeper dive into the technology.
- Design
- Tools
- Reference
- Reporting
- Data Analytics
- AI and Machine Learning
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