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Have you or are you about to invest in Azure Databricks? If so, the new Spark offering in Azure Synapse Analytics is likely to have grabbed your attention and rightly so. Why is Microsoft putting yet another Spark offering on the table and what does it mean for you?

For years we have been building modern cloud data solutions on Azure and helping our customers transform their use of data to drive outcomes. Here are 5 reasons why Azure Synapse Analytics might just be the service that we have been crying out for.

Configuring model properties in Power BI allows you to create a model which is far more discoverable and is able to better support the visualisations you need. There are several different model properties which can be configured, some of these focus on discoverability whilst others allow you to alter the ways in which data is sorted/displayed/summarised in the reports.

Learning DAX and Power BI – CALCULATE

by Carmel Eve

This is the final blog in a series about DAX and Power BI. This post focuses on the CALCULATE function, which is a unique function in DAX. The CALCULATE function has the ability to alter filter contexts, and therefore can be used to enable extremely powerful and complex processing. This post covers some of the most common scenarios for using CALCULATE, and some of the gotchas in the way in which these different features interact!

This is the sixth blog in a series about DAX and Power BI. This post focuses on relationships and related tables. These relationships allow us to build up intricate and powerful models using a combination of sources and tables. The use of relationships in DAX powers many of the features around slicing and page filtering of reports.

Learning DAX and Power BI – Table Functions

by Carmel Eve

This is the fifth blog in a series on DAX and Power BI. This post focuses on table functions. In DAX, table functions return a table which can then be used for future processing. This can be useful if, for example, you want to perform an operation over a filtered dataset. Table functions, like most functions in DAX, operate under the filter context in which they are applied.

Building a proximity detection pipeline

by Carmel Eve

At endjin, our approach focuses on using scientific experimental method to support the creation of fully proved and tested decision making, and the use of scientific research to support our work. This post runs through how we applied that process to creation a pipeline to detect vessel proximity.
This is an example which is based around the project we recently worked on with OceanMind. In this project we helped them to build a #serverless architecture which could detect vessel proximity in close to real time. The vessel proximity events we detected were then fed into machine learning algorithms in order to detect illegal fishing!
Carmel also runs through some of the actual calculations we used to detect proximity, how we used #data projections to efficiently process large quantitities of incoming data, and the use of #durablefunctions to orchestrate the processing.

Learning DAX and Power BI – Aggregators

by Carmel Eve

This is the fourth blog in a series about DAX and Power BI. We have so far covered filter and row contexts, and the difference between calculated columns and measures. This post focuses on aggregators. We cover the limitations of the classic aggregators, and demontrate the power of the iterative versions. We also highlight some of the less intuitive features around how these functions interact with both filter and row contexts.

Wardley Maps are a fantastic tool to help provide situational awareness, in order to help you make better decisions. We use Wardley Maps to help our customers think about the various benefits and trade-offs that can be made when migrating to the Cloud. In this blog post, Jess Panni demonstrates how we used Wardley Maps to plan the migration of OceanMind to Microsoft Azure, and how the maps highlighted where the core value of their platform was, and how PaaS and Serverless services offered the most value for money for the organisation.

This is the third blog in a series about learning DAX and Power BI. The first two blogs focused on filter and row contexts. We are now moving on to talk about calculated columns and measures. These are the main features used to support the display of complex visuals. They allow you to combine columns, aggregate values, reformat data, and much more. The difference between these features can get a bit confusing so we’ve attempted to make that clearer using some concrete examples!

Office 365 Wardley Mapping Templates

by Jess Panni

We use Wardley Mapping as a technique to give us situational awareness in our technical decision making process. We’re sharing our Office 365 Templates for PowerPoint and Visio, so that you can make use of them too.

Optimising C# for a serverless environment

by Carmel Eve

In our recent project with OceanMind we used #AzureFunctions to process marine vessel telemetry from around the world. This involved processing huge quantities of data in close to real time. We optimised our processing for a #serverless environment, the outcome of which being that the compute would cost less than £10 / month!

This post summarises some of the techniques we used, including some concrete examples of optimisations we made.

#bigdata #dataprocessing #dataanalysis #bigcompute

The application of scientific experimental process to software development leads to the development of fully-validated solutions. This approach provides you with confidence in designs and means that you can quickly identify ideas which are not worth pursuing.

At endjin we use the ideas of hypotheses and experimentation when designing any solution and this gives us full confidence in the designs we produce. In this post we outline the steps and advantages of using this approach.

Learning DAX and Power BI – Row Contexts

by Carmel Eve

Here is the second blog in a series around learning DAX and Power BI. This post focuses on row contexts, which are used when iterating over the rows of a table when, for example, evaluating a calculated column. Row contexts along with filter contexts underpin the basis of the DAX language. Once you understand this underlying theory it is purely a case of learning the syntax for the different operations which are built on top of it.

Help for the new CTO: Getting to know your team

by Matthew Adams

As part of my series on guidance for CTOs, I discuss using the Office of the CTO (OCTO) approach to management, its strengths and limitations.

Learning DAX and Power BI – Filter Contexts

by Carmel Eve

Here is the first in a series of blog posts around understanding DAX and Power BI. This post focuses on filter contexts. which are a central concept which is vital for being able to write effective and powerful DAX!

In this series Carmel walks through the main ideas and syntax surrounding the DAX language, and provides examples of using these over a dataset. DAX is an extremely powerful language. Using these techniques it is possible to build up complex reports which provide the insight you really need!

Salaries. What a nightmare! Hardly anyone likes talking about money. Technical people don’t like talking about money. Even a lot of sales people don’t like talking about money. When a CTO comes into an organization (even a brand new start-up) one of the first things you need to sort out is the salary quagmire. In this article we look at the strategies and pitfalls of introducing open, capability-based pay levels for a product development team.

Help for the new CTO: IR35 and hiring developers

by Matthew Adams

It has been a staple of IT projects to make liberal use of short-term contract staff. Upcoming changes in IR35 for medium to larger employers is seriously disrupting the IT recruitment market, and you should understand the impact bt

In this post we show how a combination of Kubernetes, Azure Durable Functions and Azure API Management can be used to make legacy batch processing code available as a RESTful API. This is a great example of how serverless technologies can be used to expose legacy software to the public internet in a controlled way, allowing you to reap some of the benefits of a cloud first approach without fully rewriting and migrating existing software.

NDC London 2020 – My highlights

by Ed Freeman

Ed attended NDC London 2020, along with many of his endjin colleagues. In this post he summarises and reflects upon his favourite sessions of the conference including; “OWASP Top Ten proactive controls” by Jim Manico, “There’s an Impostor in this room!” by Angharad Edwards, “How to code music?” by Laura Silvanavičiūtė, “ML and the IoT: Living on the Edge” by Brandon Satrom, “Common API Security Pitfalls” by Philippe De Ryck, and “Combatting illegal fishing with Machine Learning and Azure – for less than £10 / month” by Jess Panni & Carmel Eve.

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