The Clearly Podcast

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AKA: SharePoint - What is it good for?

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? Navigating the World of Databases ?

In the ever-evolving terrain of data management, making informed choices about the right database technology can significantly impact your business operations and strategy. From SQL and Dataverse to Data Lakes and, funnily enough, Excel, each platform serves unique needs and applications.
 
In our podcast discussing this topic, we embarked on an enlightened journey through the world of databases, exploring how these technologies compare, contrast, and complement one another in the vast landscape of data management.

? Key Takeaways:

SQL stands as the time-tested foundation for structured data storage and management, perfect for businesses seeking reliability and scalability.

Dataverse emerges as the user-friendly contender, designed with the non-technical user in mind, offering predefined tables and seamless integration with the Power Platform and Dynamics 365.

For handling enormous analytical workloads, Data Lakes offer a cost-effective solution, capable of storing petabytes of data in their native format.

Excel is an ironic inclusion, while most data professionals agree Excel is not a database, they?d also (probably) agree it?s the most widely used data source.
 
Choosing the right database technology is more than a technical decision?it's a strategic one. Whether your business requires the robustness of SQL, the accessibility of Dataverse, the analytical prowess of Data Lakes, or even the simplicity of Excel, there's a solution that fits your needs.

For a deeper understanding of these technologies and how to align them with your business goals read our latest blog post. Let's demystify the database landscape together, ensuring your data management strategy is not just effective but transformative.

https://clearlysolutions.net/blog/navigating-the-database-landscape-data-lake-sql-dataverse-and-excelnbsp

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In the last of our Machine Learning Trilogy and final episode of Season Two, we talk about applying ML in the context of Power BI. We once again try to trick the algorithm with mentions of Excel, and end with a summary of our thoughts on Machine Learning. 

Artificial Intelligence in a more general sense is also the topic of this year's Reith Lectures.  Just to prove how important and topical The Clearly Podcast really is.

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

Our highly anticipated Part Two to our Season Two Grand Finale on Machine Learning!

This week we discuss how to decide if machine learning is the right choice for you; Do you have enough data? Are you prepared to be transparent about how you analyse customer data? Will your data create an AI monster?! 

Next week, in the last of our mini-series, we will look at how you can use Machine Learning inside Power BI and other tools.

Artificial Intelligence in a more general sense is also the topic of this year's Reith Lectures.  Just to prove how important and topical The Clearly Podcast really is.

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

As a big finale to Season 2, we thought we'd bring you a mini sub-series on possibly the biggest buzz word of the year: Machine Learning.

This week, we look at what machine learning is, and where you might have come across it in your day to day life.  We go on to discuss why business might want to use Machine Learning and the sorts of problems it can solve.

Next week we will go on to talk about the considerations you will need if you want to use Machine Learning and in the final episode we look at using ML components inside Power BI and other tools.

Artificial Intelligence in a more general sense is also the topic of this year's Reith Lectures.  Just to prove how important and topical The Clearly Podcast really is.

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

This week, we talk to Haseet Sanghrajka from City Dynamics about Microsoft Dynamics and Power BI.

Well, that was what we were meant to talk about.

It?s difficult to approach this subject without starting with the range of reporting options used by Dynamics customers. And it is a broad range from our old friend Excel, to Jet Reports and FRX, Power BI and many more in between. Haseet takes us through the choices and use cases for the multiple options out there.

We also talk about how the life of the Dynamics partner has changed over the last 20 years. Personal indulgence on my side.

We end with a discussion on how Dynamics customers are specifically adopting Power BI as their chosen reporting/BI application. Ease of purchase and price point has been a significant contributor to why many customers start Power BI projects. And once it?s started they see all of that BI goodness?

Haseet was a fascinating source of insight on this subject and if you have any interest in the intersection between Dynamics and how customers consume data ? this is the one for you.
 
If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

In this week's Clearly Podcast our friend Jon Styles makes a second appearance to talk about the current job market. In season 1, episode 11 "So You Want To Be a Power BI Consultant", we talked about how to get skilled and approach the job market as a Power BI consultant. This episode continued that theme, albeit with a heavy focus on the current job market and what that means for candidates looking to move job or enter the market.

So what does the market look like right now?

As we come out of the pandemic restrictions there's high demand for experienced IT consultants across a broad range of disciplines. In the implementation partner space which remains a big employer and currently has the highest demand, we're seeing poaching of staff between partners.The demand for inexperienced individuals is far lower as employers want new hires that can be deployed on projects immediately.

What does this means for you? 

If you're experienced, there's a thriving market out there.

If you're inexperienced we talk through some strategies to help you get into the current market.

Leverage your past experience. Do you have detailed vertical knowledge or professional skills that can be easily cross-trained? Remember the basics of job hunting. Use a tailored and concise 2 page CV/Resume, do your research and prepare for interviews.Work with 2-3 experienced and well connected recruiters.

We also discuss what feels like a continuing challenge with the job market - capacity. There simply isn't enough resource to meet the current demand. We've been here before and we suspect we'll be here again.

This week we talk about data lakes.  Essentially, a data lake is a mechanism to store large quantities of (typically) raw data, both structured and unstructured, bringing together data from across an organisation.

In a "traditional" data warehouse solution,  we tend to think about an "Extract, Transform and Load " process, extracting the data from source, transforming it for analysis, and loading it into the data warehouse.  With a data lake, the approach tends to be "Extract, Load, and Transform", data is extracted from source, loaded into the data lake, then transformed when needed. 

This can simplify the process as there is no need to transform it for every scenario at build time - so we can speed up implementation.  The down side of course is that we have to do more work at run time.  As such, there is probably not an either/or situation with data lakes vs more structured systems.

The flexibility of data lakes makes it tempting to dump anything and everything into the data lake.  If this starts to happen without any curation, you are likely to end up in more of a data swamp.  Data lakes are not a way to avoid governance.

The main cloud players all offer some sort of data lake:
Azure Data Lake
AWS Data Lake
Google Data Lake

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

This week we discuss Azure Synapse Analytics

This is, in essence, a cloud-based distributed database system.  It is aimed at larger scale analytics applications rather than transactional processing.

The approach taken by Synapse to processing queries is to break them down and process parts of a query across different computing nodes.  The result sets are returned to a control node where the final result is processed.  If, for example, you request an average of a field, the control node will request the various compute nodes to calculate the sums and record counts, that can be returned and recombined into the average originally requested.

It is important to note that the higher performance in processing analytical queries tends to come at the expense of concurrency - but in an analytical application, this tends to be less of an issue.

Finally, we should also note that given the price point of Synapse, any company embarking on a data analytics journey with any expectation that their data may get large, should seriously consider Synapse as part of the tool set they are considering.

More about Synapse can be found here.

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

This week we go deep into Dataflows in Power BI.

Dataflows are a method of building reusable content in the Power BI service that other users can use to help build other models. By using Power Query in the cloud, you?re able to perform transformations on one or many entities, storing those transformations as a cloud-based service. When you come to build or extend a model, the transformed entity is available, so you don?t need to recreate all of the steps to make the entity easier to use.

We talk through the benefits of using dataflows and who we think they?re for. We also discuss when you wouldn?t want to use this method, relying on the ?traditional? desktop tools.

As we don?t see this as a replacement for Power BI desktop, at least anytime soon, we position dataflows as a tool that will benefit you in certain conditions. 

Documentation on dataflows can be found here https://docs.microsoft.com/en-us/power-bi/transform-model/dataflows/dataflows-introduction-self-service

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

In this episode we talk about how we work with social media to enhance our professional careers. Most of the conversation is focused on Linkedin.

To bring expertise to the conversation we were joined by Linkedin instructor and regular contributor, Helen Wall. 

In this episode we cover:

Ideas on how to get started creating contentOur views on the best way to write your contentInteracting with fellow users of the platformThe benefits of investing your time on Linkedin

All peppered with examples of when we created content that engaged the platform and when we didn?t.

If you?re looking to start generating content for Linkedin, this is the episode for you - we use BI examples, but the conversation is applicable for almost anyone.

As this is the Linkedin episode our profiles are:

Helen - https://www.linkedin.com/in/helenrmwall/

Tom - https://www.linkedin.com/in/tom-gough-b1725a50/

Shailan - https://www.linkedin.com/in/shailan-chudasama-202b23b/

Andy - https://www.linkedin.com/in/andyclark3/

If you already use Power BI, or are considering it, we strongly recommend you join your local Power BI user group here.

To find out more about our services and the help we can offer, contact us at one of the websites below:
UK and Europe: https://www.clearlycloudy.co.uk/
North America: https://www.clearlysolutions.net/

If you?re after a clickbaity title - this is the one for you (our podcasts with ?Excel? in the title generally get more downloads).

But, Excel and Power BI continue to be BFF?s for many of our users and as Microsoft develop more functionality that binds them together, that case will only get stronger.

We can get purist about data structures so when the term ?Excel as a database? is seen or heard we can get a little sensitive. That said, we use Excel alongside Power BI in almost all of our projects so we wanted to talk best practices for doing so.

Some examples of Excel working beautifully alongside Excel are:

Excel reports from line of business applications in a SharePoint folder feeding a Power BI modelProof of concepts. Quickly model and change data to make a concept work quicklyQuick and slightly dirty cleansing (recent example of a 20 year old business application where we didn?t want to mess with the database but needed to change a reporting structure)

So please forgive the clickbaity title but we believe, when deployed correctly, Excel and Power BI are BFFs.