Microsoft Ignite - watch live

Microsoft Ignite is happening this week. Unfortunately I won't be there but the keynote and some deep dive sessions will be streamed live. I am looking forward to seeing what Microsoft CEO Satya Nadella shares as his vision for the future of tech. I will be interested to see what other tools and technologies will play an important part in the next year and be excited to see how data fits into this forthcoming vision. 

To watch the live stream, the meeting invite is for

Start Time: 09:00 - 17:15 (UK time 14:00)
Date: Monday 24 September 2018
Time Zone: Eastern Time (US and Canada) 

Azure Cosmos DB multi-model database

Azure Cosmos DB has to be one of my favorite databases due to the breadth of available database types, its choice of consistency models and elastic scale out.

An introduction can be read here.

A definition for each of these types of databases is given.

Key-value
A key-value pair (KVP) is a set of two linked data items: a key, which is a unique identifier for some item of data, and the value, which is either the data that is identified or a pointer to the location of that data. Key-value pairs are frequently used in lookup tables, hash tables and configuration files.
https://searchenterprisedesktop.techtarget.com/definition/key-value-pair

Column
A column-oriented DBMS (or columnar database management system) is a database management system (DBMS) that stores data tables by column rather than by row.
https://en.wikipedia.org/wiki/Column-oriented_DBMS

Document
Document stores, also called document-oriented database systems, are characterized by their schema-free organization of data.That means records do not need to have a uniform structure, i.e. different records may have different columns. The types of the values ​​of individual columns can be different for each record. Columns can have more than one value (arrays). Records can have a nested structure. E.g. MongoDB
https://db-engines.com/en/article/Document+Stores

Graph
A graph database, also called a graph-oriented database, is a type of NoSQL database that uses graph theory to store, map and query relationships. Every node in a graph database is defined by a unique identifier, a set of outgoing edges and/or incoming edges and a set of properties expressed as key/value pairs.
https://whatis.techtarget.com/definition/graph-database

The five consistency levels offer predictable low latency guarantees and multiple well-defined relaxed consistency models.

Consistency Levels and guarantees

Consistency Level	Guarantees
Strong	Linearizability. Reads are guaranteed to return the most recent version of an item.
Bounded Staleness	Consistent Prefix. Reads lag behind writes by at most k prefixes or t interval
Session	Consistent Prefix. Monotonic reads, monotonic writes, read-your-writes, write-follows-reads
Consistent Prefix	Updates returned are some prefix of all the updates, with no gaps
Eventual	Out of order reads

There is a useful capacity planer that looks at request units throughput per second, request unit consumption and the amount of data storage needed by your application.

Hortonworks Data Analytics Studio and Open Hybrid Architecture

Hortonworks has announced the general availability of Hortonworks Data Analytics Studio (DAS). A new service to enable enhanced productivity of business analysts by delivering faster insights from data at scale. DAS is part of the Hortonworks DataPlane Service (DPS). DPS enables businesses to discover, manage, govern and now optimize their data spread across hybrid environments. DAS leverages open-source technologies such as Apache Hive to share and extend the value of a modern data architecture in heterogeneous environments. It includes a useful database heat map.

Hortonworks have also shared the Open Hybrid Architecture Initiative, designed to enable big data workloads to run in a hybrid manner across on-premises, multi-cloud and edge architectures.

The Open Hybrid Architecture initiative will

• De-coupling storage, with both file system interfaces and an object-store interface to data.
• Containerizing compute resources for elasticity and software isolation.
• Sharing services for metadata, governance and security across all tiers.
• Providing DevOps/orchestration tools for managing services/workloads via the “infrastructure is code” paradigm to allow spin-up/down in a programmatic manner.
• Designating workloads specific to use cases such as EDW, data science, rather than sharing everything in a multi-tenant Hadoop cluster.

AI the art of the possible

During SQL Saturday Cambridge I attended a session by Terry McCann on using AI to write a session submission to SQL Saturday. It was a great session and I would recommend you attending it if you get a chance.

In the new data world it is important to understand the difference between AI, Machine Learning and Deep Learning.

Image : https://www.argility.com/argility-ecosystem-solutions/industry-4-0/machine-learning-deep-learning/

Then breaking this down further the differences between how machine learning works and deep learning is shown here. Deep learning is really a black box.

Image : https://www.upwork.com/hiring/for-clients/log-analytics-deep-learning-machine-learning/

Terry mentioned a free book to read to learn more Neural Networks and Deep Learning. 

He mentioned also the book Harry Potter and the Portrait of what Looked Like a Large Pile of Ash which was written by an AI bot.  I hadn't come across this before but it lets you see the art of the possible in the future.

Image: https://imgur.com/gallery/gkLFz

Azure Data Factory Data Flows

There is a preview for a new feature called 'Data Flows' that enables visual data transformation capability within Azure Data Factory (ADF). This is scaled out using Databricks. This is available in the ADF Resource Explorer. Data Flow should enable a deeper understanding of your data. Monitoring and inspecting pipelines can be done in ADF. The transformations occur inside Azure Databricks which uses the Spark engine to distribute data across partitions. 

References

Microsoft Azure Data Factory documentation for Data Flow during preview is available here: https://aka.ms/adfdataflowdocs

Azure Data Factory: Visual Data Flows for Data Transformation (Preview)

Azure DevOps Services

Microsoft have announced new Azure DevOps services than span the breadth of the development lifecycle to help developers ship software faster and with higher quality. Azure DevOps includes:

Azure Pipelines

CI/CD that works with any language, platform, and cloud. Connect to GitHub or any Git repository and deploy continuously. 

Azure Boards

Powerful work tracking with Kanban boards, backlogs, team dashboards, and custom reporting. 

Azure Artifacts

Maven, npm, and NuGet package feeds from public and private sources. 

Azure Repos

Unlimited cloud-hosted private Git repos for your project. Collaborative pull requests, advanced file management, and more. 

Azure Test Plans

All in one planned and exploratory testing solution. 

PowerBI Report Server

Power BI Report Server is similar to SQL Server Reporting Services (SSRS). Power BI Report Server is on premises, and hosts paginated reports in addition to the Power BI features. There are several types of reports

• Paginated (standard SSRS type reports)
• Interactive (PowerBI Desktop)
• Mobile
• Analytical (Excel)

PowerBI Pro enables sharing and collaboration with the following features 

• Build dashboards that deliver a 360-degree, real-time view of the business
• Keep data up-to-date automatically, including on-premises sources
• Collaborate on shared data
• Audit and govern how data is accessed and used
• Package content and distribute to users with app

There is increased functionality within PowerBI Pro. A comparison between the free PowerBI desktop edition and Pro version is in the table below. Only Pro users can publish content to app workspaces, consume apps without Premium capacity, share dashboards and subscribe to dashboards and reports. Free users can connect to all data sources using connectivity options such as DirectQuery, live connection and use the data gateway. 

Licensing Power BI Report Server

Power BI Report Server is available in two different license modes: 

• Power BI Premium  
• SQL Server Enterprise Edition with Software Assurance.

A Power BI Premium license enables creation of a hybrid deployment (cloud and on-premises).

Capacity

The session delivered by Isabelle Van Campenhoudt at SQL Saturday Cambridge shared this useful capacity planning  paper. It is based on the sample Power BI Report Server topology using virtual machines. 

References

Pricing

PowerBI Free vsPro comparison

Comparing PowerBI Report Server and the Power BI service

What is PowerBI Report Server?

Capacity Planning