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James Beresford

PowerBI Deployment Whitepaper

By Enterprise PowerBI No Comments

In this PowerBI deployment whitepaper excerpt, we discuss how deploying PowerBI at scale presents a range of issues. Much of it comes from how an organisation grows. Setting the time aside to address the nascent issues is not important in a business’s early life, nor is the impact of them apparent enough to make them worth addressing. For less experienced executives there are the pitfalls of not even knowing there are issues building up. Often gaps can be patched with a bit of human ingenuity, effort – and of course – Excel.  In our view there are four key issues that converge to lead to common mistakes and wasted costs.  


PowerBI deployment challenges

PowerBI deployment challenges


First is access. Working with data is often viewed to be something best left to specialists, propeller head techies or the “number crunchers” in finance. Workers are left data illiterate and dependent on someone else to do the work – and thinking – for them. Scary, weeks long self-study technical courses reinforce this idea. What is usually needed is content and training targeted to the audience. An executive may just need 5 minutes of focused education on a dashboard pertinent to them, and only the analyst will need the weeks long course.  

Second is quality. Systems have improved significantly in their ability to filter their front-end input so that the correct types of data are captured, but still users find a way to enter data in the wrong place, format or not at all if it doesn’t help them complete their task. More challenging in modern environments is the array of systems involved that simply don’t relate to each other at scale. A frontline worker may remember all the different codes that relate to a given customer or product, but a bulk data analysis system does not and is unable to relate them. Good data quality is recognised in the literature as one of the key factors in ensuring a successful implementation alongside governance of that quality.  

Third is discoverability. Even in only moderately complex organisations data is used, reused & recycled with next to no traceability. This leads to duplicated effort, inconsistent definitions, that then drives contention within the business as people disagree over what is the right way or measuring progress. Access is also often siloed, with line of business or system owners being protective over what they see as their data, wary of how others may interpret it.  

Last is governance – a polite way of saying ownership and management of data. People in the organisation need to care for, manage and nurture their data – KPMG state that “Data is now the most significant asset many organizations possess” – and as such needs to be cared for – but like all intangible things it is easily forgotten about. Businesses that are prepared to put a value on that asset are few and far between, and most often only realise its value when a core system experiences an outage. 


This is an excerpt from our Enterprise PowerBI Whitepaper – please follow the link to read all the content – it’s free & there’s no sign up required.

Need help after reading this piece of our PowerBI Deployment Whitepaper? At Talos we have defined our PEBBLE Enterprise PowerBI Methodology to help organisations drive success in deploying PowerBI as a complete self service analytics platform. If you are struggling with any of the challenges discussed above, we might be able to help. Please get in touch if you’d like to have a discussion.

Cheers, James

BI Challenges

By Enterprise PowerBI No Comments

Do any of these BI Challenges sound familiar? Does your business run on high risk, ungoverned spreadsheets that nobody apart from their original creator really understands? (Boldly assuming they are still with your organisation). Do you frequently clash with your peers over who has the right version of the numbers? Is there a team of analysts and number crunchers beavering away to produce figures each month? Is that team duplicating effort by other departments? Do you even know if they might be? Do your peers readily share their data?

All these issues are common throughout modern businesses despite the means of eliminating them being readily available. There are of course huge benefits to be obtained by becoming a data driven organisation which is why many industries invest significantly in being able to use their information to improve their business.

Benefits of being Data Driven

Benefits of being Data Driven

Getting its house in good order and overcoming these BI Challenges allows an organisation to quickly realise the benefit of simply having reporting happen automatically, instead of being a panicked, last-minute activity for already overburdened analysts. This frees up the analytical capability of the business to use analysts to add greater value by identifying the opportunities and risks that data can reveal.

Leaders then can realise the benefits of having a 360-degree view of the organisation – from sales through to productivity – and change the track of business in real time, instead of waiting for a report with data from the last quarter and trying to correlate that with others in a mental juggling act. Finally, the improved window on data quality allows the data to be improved to the point where it can support automation within the business – another key pillar for Efficient Decision Making. Leaders are often uncertain of how to quantify the benefits from undertaking these often-challenging activities, but if you simply look around, the Financial Services sector is a heavy investor in this space, and let’s face it, banks aren’t going to be investing if there isn’t a good ROI.

Data and analytics veterans often express a degree of frustration that we are still trying to solve the same problems we were decades ago. However, most of us have come to accept this is how businesses grow and mature in their information usage. Some of these steps are virtually inevitable as an organisation grows in capability, complexity, and capacity. Gartner’s Information Management Maturity Model has been in existence for 20 years describing exactly this journey

BI Challenges described by the Gartner Information Management Maturity Model

Gartner Information Management Maturity Model

There are few shortcuts to solving these BI Challenges, but the difficulty level has been decreased in recent years. So, what has changed to make these problems more solvable? Simply, the evolution of user friendly, cloud based, pay by usage data & analytics technologies has massively lowered the barriers to entry. The ability to start an enterprise grade journey has stopped being an expensive up-front expenditure and is now – in theory – something any organisation can do.

This is an excerpt from our Enterprise PowerBI Whitepaper – please follow the link to read all the content – it’s free & there’s no sign up required.

At Talos we have defined our PEBBLE Enterprise PowerBI Methodology to help organisations drive success in deploying PowerBI as a complete self service analytics platform. If you are struggling with any of the challenges discussed above, we might be able to help. Please get in touch if you’d like to have a discussion.

Cheers, James

PowerBI governance

The need for good PowerBI Governance

By Enterprise PowerBI No Comments
What do we need PowerBI Governance for? Well, PowerBI has come a long way in the past decade – and yes, it has been a decade. It was released way back in July 2011! What was a humble reporting tool is now a complex ecosystem of self service analytics, data management and artificial intelligence. While the advancements in themselves are great, with greater complexity comes a greater need to understand and manage it through PowerBI Governance, especially at the Enterprise scale.

What needs governing?

In my experience across a range of implementations there are 4 key areas that need formal management:

  • Data
  • Security
  • Platform
  • Users

I’ll run through each of these below in more detail.

PowerBI Governance – Data

PowerBI governance data

Depending on the size and maturity of the organisation, data governance may already be in place. If so, this part of the design of the PowerBI governance model is simple. The existing policy can directly inform your approach.

However if it is absent, then part of designing the governance model includes creating it. In the early part of a deployment lifecycle, where PowerBI reports are simple and departmental, accountability for data is often pretty simple; the department that creates the report knows data owners and can manage issues as they arise. However once the reach of PowerBI scales these links become less clear.

If you are managing PowerBI centrally in an organisation, and a data item is suspect, how does it the investigation process work? How does the organisation decide on where to allocates its limited development resources if demands from different areas are in contention? How do we prevent disparate teams duplicating efforts? Who is accountable for maintaining the data catalog that makes assets discoverable? Who decides who can see what data when it is discovered?

All these questions fall under Data Governance and answering them is critical to ensure a well managed self service analytics environment.

PowerBI Governance – Security


It is becoming cliché to say it, but data is a valuable asset. I’ve written before about the security risk associated with PowerBI desktop but like all data stores it has many attack surfaces and holes to leak from. Managing them correctly and actively is essential to prevent embarrassing and potentially expensive data leaks. As with all issues to do with governing technology risks, there are a mix of hard (technical) and soft (policy) tools you can bring to bear to the problem.

On the “hard” front are the platform level controls you can put in place. Some of these sit at a purely PowerBI level, such as the ability to limit insecure external sharing via publish to web. Other controls need the engagement of Azure administrators through deploying tools such as Azure information protection to keep an eye or lock on sensitive data.

On the “soft” front, giving education on the risks of data loss, costs of data leakage and how it happens is effective. It is not reasonable to expect untrained users to foresee the unexpected consequences of downloading and emailing a copy of a report. Most data breaches are caused by human error rather than any malicious activity. Education is key to this issue.

Thus the PowerBI platform needs to have basic guidelines established for its use, and then communicated around the organisation. It’s not a set and forget activity either – the technical environment and the business it serves changes. Once again, good ongoing governance is essential to keeping your platform and data secure.

PowerBI Governance – Platform


PowerBI is a complex beast. The admin portal overview page alone is now a half hour read! There are controls over the use of capacity, what is able to be shared and how, what visuals can be used and even how the portal can be customised to match your organisational branding. Then there are the requirements to monitor the platform for usage and capacity. This includes on-premise data gateways – which aren’t part of the services management capability.

On top of this is decisions to make around the usage and administration of Workspaces. End users should be given flexibility to self serve, but designing controls around data access is vital. Preventing scenarios like someone accidentally sharing HR reports with everyone’s salary details in them requires planning.

While it is IT’s role to administrate the platform, the data on it is a business asset and so the governance process needs to be a joint effort.

PowerBI Governance – Users


Last – but definitely not least – are the users of all this capability. Rolling out PowerBI across the enterprise means you need to support and enable the users through a managed program. How are you establishing your Centre of Excellence to ensure quality content gets built and delivered to stakeholders? How can you drive an internal PowerBI community to support the growing capability of self sufficient analysts? Who will design and manage the training program to the different audience types that need to be catered to?

Plus of course is the balance of how to licence everyone. Is PowerBI premium the right option, or can you get by on PowerBI Pro licences for now? What is the trigger to make the change?

Driving the platform to deliver value to the business is not something that will happen by accident. Data literacy is not a native skill to many workers. The process of infusing that in your business needs to be managed.


This article aims to highlight some of the key concerns in governing PowerBI across the four dimensions of Data, Platform, Security & Users. As you have undoubtedly been gathering there has been a growth in complexity of the ecosystem. This has led to a similar complexity in terms of how the platform and its use needs managing.

If you need to hit the fast forward button on all this, we can help. All this complexity falls under the first step in our PEBBLE Enterprise PowerBI methodology – Plan. Our PowerBI Governance framework addresses these concerns – and more. Please reach out if you would appreciate some help.

Popular BI – State of the Self Service BI market Jan 2022

By Automation Initiation, Data & AI, Data Visualisation, Enterprise PowerBI No Comments

Popular BI Tools in 2022

This is an update on a series of posts I have written over the last few years looking at the relative popular BI Tools (2019’s is here). I did try to expand my search to cover more platforms but there are still only three that seem to really matter.

Trying to get actual usage figures of any Self Service BI tool is pretty difficult – none of the big vendors will willingly release figures – and if they did they’d probably be suspect.

But in analytics sometimes there are useful proxies which, while not as accurate as hard numbers, can give a useful perspective. In this case, we will use our friend, google trends:

Tableau is Red, PowerBI is Yellow & Qlik is Blue.

A quick note on methodology – I’m looking for Qlik (Software Company), Tableau (Data Visualisation Company) and Power BI (Software). I restricted the search to the US because Tableau is also French for “Table” so a worldwide search gets noise from that as well.

State of the Self Service BI Market

What you can see is that PowerBI has caught up with and slowly started overtaking Tableau as of early 2021. Tableau no longer appears to a leader in the self service field, with PowerBI looking to dominate. Qlik is continuing its slide into irrelevance. From this data we get a bit more insight – search volume across all three has been declining from its peak in 2019, now at 80% of its height in 2022.

Next up if we look at market share rather than sheer numbers, we see something interesting. In 2016 Tableau held about 70% of the searches, which has now dropped in 2021 to 46% (and still falling). More interestingly Qlik’s share has fallen to about 5% of the market (compared to 18% in 2015) but Power BI’s share has grown to about 49% (and still rising), compared to 8% in 2015. From the chart there was quite a change in velocity in Tableau searches from early 2020 (in line with the acquisition by Salesforce). It is also worth underlining the fall in share for Qlik is also based on declining search volumes overall.

What does the future hold for Popular BI tools?

Based on trends to date I would make the following headline predictions for the Popular BI tools market in 2022:

  • The Self Service BI market is not as hot as it once was, the hype having moved on
  • Power BI will continue to experience strong growth and will consume more market share, whereas Tableau’s growth will fall
  • QlikView will continue to decline, and no major competitors will arise either

These findings confirm my view held since 2018 – confirmed by my market feedback – that Qlik is a dead platform walking. It’s failed to catch up with market changes and is simply a legacy product. It’s squeezed between the two with no compelling reason to be chosen. However with Salesforce acquiring Tableau, it seems to have gone into a vendor locked decline (in a similar manner to products that have fallen into the SAP or IBM fold in older days). PowerBI has an almost empty field in which to compete.

Competing with PowerBI is going to be a tough proposition as any challenger will need the all encompassing Data Platform juggernaut of Azure behind it (excuse my hyperbole) which gives it the enterprise capability needed to succeed long term. Effectively only Google or Amazon could hope to do so.

However, Google and Amazon’s offerings, (Data Studio & Quicksight respectively) still lack much market traction at this point. The acquisition of Looker seems not to have impacted Googles presence much, despite having 3 years to do so.

My previous predictions have pretty much held true, but as Yogi Berra famously said, “It’s tough to make predictions, especially about the future”. I can be certain that it will be another exciting year in Data & AI. We specialise in Enterprise PowerBI so contact us if you need some help on your journey.

3 faces of Enterprise PowerBI Training

The 3 faces of Enterprise PowerBI Training

By Enterprise PowerBI One Comment

Since Self Service BI became an actual thing we have advised many organisations on how to roll it out successfully and give the best ROI as part of our Enterprise PowerBI Training solutions. A key mantra for me has always been to tune the content to the audience. After all, you book The Wiggles for your children’s party, not a heavy metal band (well, unless they are into Hevisaurus).

Over the course of working with organisations to define these audiences, consistently there are 3 personas that come up, each with their own needs with regards to enablement in terms of data and training. These 3 personas are:

  • The Actor
  • The Creator
  • The Author

Lets have a quick walk through these roles!

The Actor

An Actor is reading from the script, interpreting what is in front of them but not changing it.

This user makes up the bulk of users in most organisations. Their use of data and reporting is as an input to drive or inform decision making. The individuals in these roles can range from the CEO who needs to have an at-a-glance dashboard of their organisations performance, to a field sales worker who needs to know the buying profile of their next client.

The level of interactivity with any reporting will be basic – maybe selecting a few options or filters, perhaps drilling down a pre-set path to get some finer detail. Consequently the degree of training and enablement they need is fairly light. Key information for them is where to find the report, what the data on the report actually means and what buttons to press.

The Creator

A Creator builds an vision from the script, taking it to design their performance.

This type of user is actually one of the most important in terms of organisational impact. These are the people that are tasked with generating content for the Actors, and as such have a deep understanding of the data in their domain. These are the people tasked to work with the technology experts to build out the data models that drive much of the self service capability.

These users really get into the guts of the data and understand it in depth. When an Actor asks for explanation on a particular data point they are the ones that have to investigate. The technical training they need focuses on content creation and publishing. The enablement needs to cover things like business analysis skills, Master Data Management and Data Cataloguing.

The Author

The Author of course writes the script, starting from very raw materials to build a story.

Most people calling themselves PowerBI experts sit here, and most organisations have a handful of them – they are not a big population (though in my world are a vocal one!). They sometimes fill the role of creator but more often than not are trying to make sense of the organisations data, how it interlinks and where the hidden treasure lies. They “self-serve” from the raw data, constructing new ways to get insight into the organisations performance.

Here enablement focuses on technical capability as they need to understand how to manipulate and interrelate data that may be in less than ideal forms and certainly hasn’t been through an enterprise cleaning process. Data Catalogues support them in the discovery process.

To wrap

The key message to take from this post is that when rolling out Enterprise PowerBI Training at scale these different communities and capabilities need to be addressed – and in different ways. There is no value in sending all of your team on advanced PowerBI training if the skills learned will never find a practical application. Similarly if you build it, they won’t come – you need to guide them there.

Good luck, and if you need some help or advice, please get in touch.