Be Insights Driven! Why we should not just be Data Driven, and definitely not Tool Driven. #PowerBI, #Tableau, #Qlik

I presented at a ‘BI without the BS’ event in London in November 2018. The idea was that there would be three tools and three players; Qlik, Tableau and Power BI, a judging panel, and a live audience of about 100 people. I represented Power BI and it was very clear that only a few people had seen it before.

As a data visualization person, I’m all about making things clear for people and that was why my story was much simpler and the facts were compelling, displayed in Power BI; I told a story which had a call to action.

My interpretation of the rules

My interpretation of the rules was that data storytelling was one of the main judging criteria. I had not seen the event as a product demo, and that’s why I emphasized the insights that Power BI gave me over knobs and levers that each tool can do. Product demos are easy, but not everyone can find insights in data.

Google Chief Economist Hal Varian predicted that data storytellers are the future over a decade ago. With data as the new oil, every company is seeking new ways to monetize their data. So my emphasis had been on data storytelling with a particular tool, but not trying to sell the tool itself as a demo. That’s my boxing ring to play in, and that’s the hard part of working with data.

An Equal Playing Ground for Games?

For my Power BI piece, my insights were all about the complexities in being a woman in gaming. My Power BI analysis showed that women earned just $1.8m in prize money in total, but the top male game winners earned $145m in total. See the tiny pink sliver? That’s the proportion that women earn in gaming competitions. If you’re thinking, that’s not a good dataviz to show, I can barely see the sliver – then you have missed the point. The point is, it is a tiny sliver. For colours, I have used Dark Orchid to represent female players, and Teal to represent male data throughout the visualization.

Female vs Male Prize Money in Games

So there was a huge difference. In case you need the numbers:

card

So there is a huge disparity between male and female earnings. Is this because there are less women players? Apparently not. This chart shows that the gap between male and female players is narrowing:

Male vs Female Game Players by trend
In the data, I noted that the players were ranked from 1 to 100, for each gender. So I pitted the men and women together in terms of rank to show how the first ranked male player earned versus the first ranked female player. Here is the chart, in Power BI:

Prize Money by Gender

You can see that the girls’ earnings are practically flat, whereas the male earnings are vastly higher. The gender gap in pay is real, absolutely real.

I also noted that the lowest ranked player still earned more than double what the highest earning female player did. So the data showed lots of insights; it depended if you were willing to see things that made you uncomfortable.

Then, I wondered if there was a relationship between the number of tournaments played, and the prize money won. So, I used the male data here to see if  a reasonable relationship could be inferred between the number of tournaments played, and the amount of prize money earned. If women are playing less tournaments, then naturally they will earn less. So how did that pan out?

Relationship between No of Tournaments and Game Prize Money

The interesting thing was that the total number of tournaments played (on the X axis) didn’t seem to impact the amount of prize money earned. I’d have to do more analysis but you can see a vague relationship in the hexbin chart, but with a lot of outliers. I might come back and look at that another day, using R and Python or something.

Gaming in Real Life

So my piece was more about exploring the idea that there is no equal playing ground for women in gaming, and that’s certainly borne out by some of women’s experiences in the gaming world. Harassment for women in gaming can involve sexist insults or comments, death or rape threats, demanding sexual favors in exchange for virtual or real money, or even stalking. The GamerGate scandal tells you all you need to know about it, I suppose. Alternatively, you could look at Fat, Ugly or Slutty where women record instances of instances of sexism. Warning; it is not a pretty read. Or women hiding their identity online as a female, which is a safety measure that many women take. The most recent threat against female gamer Anita Sarkeesian was in Logan, Utah on October 15, 2014. She was scheduled to deliver a speech on a Wednesday evening until an anonymous email message arrived a day before, stating that there would be the deadliest school shooting in American history if the event was held. So don’t kid yourself that this isn’t real, and the impact means that many women are excluded from feeling that they can enter competitions in gaming.

Be Insights Driven, not Data Driven, and definitely not Tool Driven

When you analyze data, you bring your own personality and insights to analyzing data. I don’t believe that tools can solve problems; I believe that we have a lot of data, but no insight, information or wisdom unless we do something with the data. I don’t like the phrase data-driven; I prefer insights-driven. Qlik, Tableau or Power BI aren’t going to solve problems for you; they will just display data that hopefully brings about insights. The insights are yours and you can use each tool equally badly if you don’t have a story or a thread, or the data isn’t provoking an insight. We were all given the same data but we got very different results. That wasn’t down to the tool; it was down to the person driving the tool.

What I thought of the Tableau piece

I liked what Chris Love ( LinkedIn ¦ Twitter ) did; he clearly knows his stuff and it was nice to meet him in person. Funnily enough, we used to have the same boss when I had a boss (hello Tom Brown!).

I did find Chris Love’s visualization more interesting because he honed in on the journey of one player from the starting point to his success in winning a lot of money, and the journey was well displayed in Tableau. Chris had a good balance of context and detail, and for me, this was the data story telling piece. Here is the image below, credit to Laura Sandford:

 ChrisLoveTableau.jpg_large

What I thought of the Qlik piece

Nick Blewden ( LinkedIn, not on Twitter) is obviously fantastic at Qlikview and he did a good job of showcasing it. To be honest, I felt out of my depth here since it was a whizz tour of the product but since I’m not familiar with Qlik, I felt a bit bludgeoned with chart after chart and I couldn’t see a clear thread; it was information load as I tried to pick up the Qlik lingo as well as follow the story. I understand that Nick’s segment wasn’t aimed at beginners in Qlik and that’s ok with me; he only had five minutes to showcase what he’d done and he did a great job.

I am not familiar with the Qlik product set but a lot of the audience clearly were, and I could hear lots of mutters about ‘good to see he’s showing that feature’. So my perspective here is that of someone who does not know Qlik but who has expertise in Tableau and Power BI.  I can look at Qlik another time, if I choose.

I felt I’d let Power BI down at that point because I had not gone down that route of doing a product demo and I feel really bad about that. I had gone for the analytics and insights part because I’d understood the rules that way, and the audience can see a Power BI demo anytime they like.

One reason for me to present at the event was that I’d seen it as an opportunity to learn more about Qlik from the session, but all I saw was chart after chart. For me, there were lots of business intelligence dashboard and that’s fine and I think that it was a good product demo.

So my lasting takeaway from the Qlik segment is this dashboard was interesting because it showed that it was quick to produce a lot of charts very quickly, but sometimes ‘less is more’. I’m a fan of Stephen Few and he talks about the importance of finding the signal in the noise, and having a ton of charts can simply mean more noise if they are not meaningful. Here is the image below, credit to Laura Sandford:

NickBlewdenQlik.jpg_large

What I’d like to see next

I think I’d have preferred a larger, more mixed audience. A lot of people seemed to know one another already and I only knew one person in the audience. I’m not part of that community and it was nice to meet new people at the end.

Honestly, I’m not a fan of being shouted at by men I don’t know; it is really unpleasant. I think that the audience members should have the courtesy to refrain from shouting out during the performance. I was really put off with people shouting ‘Come on Qlik!’ and ‘Come on Tableau’ during the event. I didn’t hear a single voice for Power BI, not that it mattered; it really disrupted my thought flows to have people shouting when you’re trying to analyse data and I found it unsettling. Being at a live event isn’t like Gogglebox where the presenters can’t hear you.

So what did I think about the Power BI vs Tableau vs Qlik debate?

So what were my takeaways?

My call to action: be Insights Driven, not Data Driven, and definitely not Tool Driven.

According to the Qlik website ‘Deliver automated insight suggestions that help users see their data in new ways, auto-generating and prioritizing analytics and insights based on the overall data set and a user’s search criteria.’ Demystifying the marketing, it seems as if this means producing a ton of charts really quickly and if that’s what you’re looking for, it certainly did that. My overriding thought was that it can produce lots of charts but I really want to find meaning in charts, and I don’t measure meaning in charts by having as many charts as possible. I just got lost and I actually don’t think that’s good for Qlik.

For Tableau, I’d like to see Tableau become a real enterprise tool and it still feels like a cog in an enterprise wheel to me. I would not do any data prep in Tableau Prep although I do have experience in it; I’d want to use Power BI dataflows to clean data so that the data and the dataflows become part of the enterprise ecosystem.

I build big systems and I need to think big. When I’ve been working for customers, I’ve found it is easier to show ROI with Tableau and Power BI but it has taken longer for people to realize ROI with Qlik.

I am eternally confused by licensing and I find Tableau’s licensing simpler; Power BI and Qlik seem to be way more confusing to me. For Power BI, I always refer the customer back to their Microsoft reseller because they can figure it out for them.

My Power BI dashboard is here, for those of you who want to play with it:

https://app.powerbi.com/view?r=eyJrIjoiOTNmMzUyODAtZGFjZC00OTUxLWIxMmQtMDYzMTA5OWU1OGRkIiwidCI6ImFmMTA4OTMyLTkxNmQtNGUwNi1hZjVmLTAyMzg0NjZiZWRiMCIsImMiOjh9

Call to Action

I have put links, credits and sources here in case you want to play with the data.

Power BI Functionality

Colour Palette Used

Teal
#066082
#068
teal
hsl(196,91,26)
rgb(6,96,130)
Orchid
#b12acf
#b3d
darkorchid
hsl(289,66,48)
rgb(177,42,207)
Sandybrown
#fed044
#fd4
sandybrown
hsl(45,98,63)
rgb(254,208,68)

References

Distribution of computer and video gamers in the United States from 2006 to 2018, by gender. Source: Statista 
Why aren’t there more women in eSports?

 

Financial Storytelling and Data Storytelling with Profitability Ratios

Following on from my earlier blog post, discussing Accounting Ratios, let’s take a look at a specific set: Profitability Ratios.Profitability Ratios can be defined as understanding the effectiveness of the company in generating profit. In this blog post, we will concentrate on profitability ratios, working our way around the flow chart presented here:

Screenshot (1)

The formula are presented below, in terms of their meaning:

  • Return on Net Assets (RONA) (Return on Capital employed) – return on the fixed and current assets less current liability. It is also known as the primary ratio.
  • Return on Equity (Return on Shareholders’ Funds) – This also looks at return on the fixed and current assets less current liability, but it looks at it from the Shareholder’s perspective.
  • Gross Profit Margin – percentage of sales revenue remaining after the expense of making the product / solution / delivering the service is taken into account.
  • Net Profit Margin – This is the percentage of sales revenue that’s left, after all of the expenses of running the firm have been fully met.

Let’s have a look at how they are calculated, and what they mean.
money-2696229_1920

Calculating the Profitability Ratios

1.Return on Net Assets (RONA) (Return on Capital employed)

Net Profit before long-term interest and tax /

Total Assets less creditors falling due within one year

This figure is expressed as a percentage, so it is multiplied by 100%. That said, at root, it is fundamentally calculated as follows, expressed as a percentage:

Profit /

Capital

Profit can include one of the following metrics:

  • Operating Profit
  • Net Profit before Interest and Taxation
  • Net profit after taxation
  • Net Profit after taxation
  • Net Profit after taxation and preference dividend

Capital can be measured by one of the following options:

  • Total Assets
  • Total Assets less intangible assets
  • Total Assets less current liabilities
  • Shareholders Funds
  • Shareholders’ Funds less preference shares
  • Shareholders’ Funds plus long-term loans
  • Shareholders’ funds plus total liabilities

What combination do you choose? Basically, the MVP answer holds here: it depends. The definitions depend on what business question you are trying to answer. The RONA definition was chosen here in order to illustrate how it differs from Return on Equity, which is explained below.

2. Return on Equity (Return on Shareholders’ Funds)

Net Profit before long-term interest and tax /

Share Capital and Reserves

This figure is expressed as a percentage, so it is multiplied by 100%.

3. Gross Profit Margin

Gross Profit /

Sales

This figure is expressed as a percentage, so it is multiplied by 100%.

4. Net Profit Margin

Net Profit before long-term interest and tax /

Sales

This figure is expressed as a percentage, so it is multiplied by 100%.

It’s possible to see that these ratios are made of five different things. I’m a visual person so I’m marking these in colour since I will need to remember them for my exam!

  • Gross Profit
  • Net Profit before long-term interest and tax 
  • Sales
  • Share Capital and Reserves
  • Total Assets less creditors falling due within one year

Interpreting the Profitability Ratios

With the Return on Net Assets figure, we are looking at the effectiveness of the assets that are financed by long-term creditors as well as the shareholders, and we are looking at the profit generated as a result of these combined assets. Higher RONA can mean that the company using its assets efficiently. Also an increasing RONA may indicate an emphasis on executing efficiently, as evidenced in improved profitability and overall performance.

The Return on Equity ratio looks at the same issue, but from the perspective of the shareholder only. The long-term creditors are partialled out. Understandably, shareholders want to see a high return on equity ratio, since this would show that the organisation is being effective in its deployment of investors’ funds. Shareholders can also track progress by calculating the return on equity at the beginning of a period and then check it again at the end of a period to see if there is a change in return.

Net Profit Margin shows the sales revenue after all of the expenses have been removed. It should be as large as it can possibly be, as long as it is sustainable. However, this should not be taking place at the expense of another aspect of the business. Be wary of short-term attitude to profit. This is sometimes evidenced in the net profit margin.

Limitations on the Productivity Financial Ratios

Accounting Ratios give us useful insights in the management of a company, but it is not the whole story. The business context, and the company itself, should also be considered. RONA does not calculate a company’s future ability to create value. Additionally, the values on the balance sheet might not represent the replacement cost, therefore masking the reality of asset utilisation.

In the next post, we will look at Activity Ratios and how they are calculated, along with some advantages and limitations. We are leading up towards visualizing these ratios in Power BI, and it’s important to understand the ‘why’ as well as the ‘how’ of visualizing these ratios.

I’m speaking at #ITDevConnections 2018!

ITDev Connections Side Banner

I’m speaking at #ITDevConnections 2018! Join me in Dallas and learn on topics such as:

  • Blockchain Demystified for Business Intelligence Professionals
  • Data Analytics with Azure Cosmos Schema-less Data and Power BI
  • R in Power BI for Absolute Beginners

There is also a Women in Technology lunch and I’m excited about that, too!

Join me in Dallas this October!

I’m excited to see that some of my SQLFamily friends are going, such as Mindy Curnett, Kevin Kline, Bob Ward and Tim Mitchell. I’m looking forward to going to sessions as an attendee, too!

You can find the agenda here.

SPECIAL OFFER:Use promo code STIRRUP by September 7 and save on your pass!*

  • All Access Pass – $1899 with code STIRRUP (a $2699 value)
    Includes Pre-Conference workshop plus 200+ sessions and networking
  • Essentials Pass – $1199 with code STIRRUP (a $1799 value)
    Includes 200+ sessions and networking

All Access Pass – $1899 with promo code STIRRUP (a $2699 value) 

Includes everything listed in the Essentials Pass, PLUS you gain access to one Pre-Conference Workshop, where you’ll spend a full day in the classroom with our experts.

Choose from 8 workshops:

  1. Migrating to Windows 10 – Notes From the Field
  2. Mastering ASP.NET Core, Angular 6 and EF Core
  3. From Beginning to Expert SQL Programmer in One Day
  4. Progressive Web Apps From Beginner to Expert
  5. ConfigMgr and Azure – A Flexible, Powerful and Compelling Combination
  6. Practical Performance Monitoring
  7. Build Intelligent Applications with A.I. Technologies
  8. Going Serverless Using Azure

Essentials Pass – $1199 with promo code STIRRUP (a $1799 value)

Includes:

  • Mix and Match 150+ Tracks/Sessions
  • Access to Session Presentation Materials
  • Vendor Receptions
  • Networking Events
  • Breakfast and Coffee Breaks
  • Networking Luncheon
  • Conference Registration Giveaway
  • and more!

*Prices increase after September 7, 2018. Must use code to receive discount. Non-transferable. Cannot be applied to previously paid registrations.

Fun DataDive with DataKind UK

This weekend, I volunteered with DataKind UK on their Summer DataDive, which took place on the weekend of 28th and 29th July 2018 in the Pivotal London offices in Shoreditch. I had a fantastic, memorable weekend, mixing with around 200 other data scientists.

I’d like to thank the DataKind team for being so inspirational, giving, and kind with their time and skills. I’d like to emphasise my absolute admiration for the Data Ambassadors and the work that they do to lift everyone up.

Why did I do this? DataKind appealed to me since it meant that I could sharpen my data science skills  by pitching in with experts. New learners to Data Science are welcome, and there were also newbies who had some experience of data and wanted to know more. There was room for everyone to contribute, so if you are a newbie, it would be a great way to join in the conversations and learn from experts who love what they can achieve with data. Plus, it’s a great opportunity to mix with real data scientists. This isn’t Poundland data science, and this is not pseudo Data Science. This is the real thing; and I spent two days immersed in real problems using Data Science as a solution. I learned a lot, and I contributed as well. There is a saying that you are the average of your friends, and I needed to get close to more Data Scientists so that I could build on my earlier experience on AI and bring it up-to-date.

I wanted to help a charity, by dedicating my time and skills, to support women and girls who need it. I understand that there are vulnerable men too; but this isn’t about whataboutism. Women and girls are disproportionally affected by issues such as domestic violence and being the victims of sexual crimes, and I wanted to do something practical to help.

Lancashire Women's Centres LogoFor my specific contribution, I was working with a team of 25 other data scientists, we worked on finding insights in data belonging to Lancashire Women’s Centre. The vision of Lancashire Women’s Centre is that all women and girls in Lancashire are valued and treated as equals. Their aim is to empower women and girls to be able to transform their lives by bringing them together to find their voice, share experiences and understanding, develop their knowledge and skills, challenge stereotypes and misconceptions about them so that they can have choices in becoming the individuals they want to be. I share this conviction deeply and I wanted to help.

You may well be thinking that the charity help a small number of women, but that’s not the case at all. They have a real impact in their community. The Lancashire Women’s Centre has helped over 3000 women in the last year. This includes 5807 hours of therapeutic support were accessed by 1154 women and 78 men.  Following therapy: 25% were no longer taking medication, 8% felt the support had helped them find and keep a job, 12% continued to access LWC services to support their recovery.

So what did I do? I can’t share specific details because the data is confidential, and it obviously impacts some of the UK’s most vulnerable women and girls. I will say that the tools used were CoCalc, R, Python, Excel and Tableau and Power BI to work with the data.

DataKind™ brings high-impact organizations dedicated to solving the world’s biggest challenges together with leading data scientists to improve the quality of, access to and understanding of data in the social sector. This leads to better decision-making and greater social impact. Launched in 2011, DataKind leads a community of passionate data scientists, visionary partners and mission-driven organizations with the talent, commitment and energy to use data science in the service of humanity. DataKind is headquartered in New York City and has Chapters in Bangalore, Dublin, San Francisco, Singapore, the UK and Washington DC. More information on DataKind, our programs and our partners can be found on their website: www.datakind.org

Lancashire Women’s Centre

DataKind JenStirrup and Team

I’m the one on the right, wearing orange!

I’m looking forward to the next one!

Tableau Prep, Power Query and Power BI – Good together?

A question I often here is this: Which tool should I use, Tableau or Power BI? The truth is: They are not mutually exclusive.

Tableau is great at business mysteries: ill-defined questions where you have to surf the data for results. Power BI is particularly great at modelling and cleaning the data, with clean, crisp data visualisation and the ability to use custom and open-source data visualizations. This blog isn’t aimed at the technical user, but at the analyst who needs to get information out quickly. I will do another post, aimed at the geeks, another time.

Tableau and Power BI are paintbrushes for your data. The tools do not have to be mutually exclusive. Power BI contains some superb data preparation functions which are aimed at business users. Speaking to customers, however, it’s clear that they aren’t aware of its functionalities. So, I decided to make your life easier for you by helping you to compare the two, using the same data with the same result.

In the first video, we will look at Tableau Prep in some detail. We will use one of the Tableau datasets, Superstore, and we will work through one of Tableau’s own tutorials.
In the next segment, I repeat the exercise using Power BI and Power Query so that you can compare more easily. Ultimately, both tools achieve the same ends.

Where Tableau Prep falls down, in my opinion, is that Tableau Prep does not handle complex pivots very well. In the World Data Bank data, the Life Expectancy data which was made famous by Hans Rosling is available, and this data needs pivoted in order to be visualized effectively. Tableau needs a lot of branching pivots to get it to work. Power BI, on the other hand, pivots it within a few clicks. What do we take away from this?

  • Tableau Prep is great for simple data preparation tasks
  • Power Query, also known as Get and Transform in Excel, is great at simple and much more complex and difficult data preparation tasks.

So, which tool you use will depend on the data prep that you need to do. If it is easy, use Tableau Prep. If it is anything above easy, or includes easy, use Power Query.

You can use Power BI to shape the data, and then use the data in Tableau. See? You don’t have to choose. Select the best paintbrush for what you need to do, and you are not restricted to one paintbrush.

To see the videos, go here:

Tableau Prep: An Overview

 

Power Query and Power BI Together for Tableau Users:

 

 

Microsoft Data Insights – Digital Transformation with Power BI for the CEO

I’m holding a series of training courses around the UK, more details will be published. In the first instance, on 15th September, I’ll be holding a day-long practical workshop on Working with Business Data for Busy Executives in SME Organisations in Hertfordshire, England. The cost will be £100 pounds plus VAT, food and workshop materials included, and you can also network and share experiences with other attendees who will also be running businesses, like you.

I don’t believe in a ‘stack ’em high’ approach, which doesn’t give a pleasant experience for learning. So, classes will be restricted to 12 people only, unless otherwise stated. This means that you will get a good amount of attention.

I’m doing the Executive MBA at the University of Hertfordshire Business School, I’ve also been a NED (Non Executive Director) for PASS, who are based in the United States.  As I’ve been spending time leading organisations, I’m keen to share this knowledge and expertise with the community from a data-driven, data leader perspective. The following blog post will give you a flavor of the workshop. along with some of my thoughts on Microsoft Data Insights Summit. If you have any questions, please pop them in the comments box and I’ll read them from there.

Here are my slides from Microsoft Data Insights Summary, combined with some of the slides from the keynote by James Phillips, held in June 2017.

Slide1

For those of you who know me, you’ll know that I have extensive experience in Tableau as well as Power BI. However, most of my consulting data visualisation is in Power BI suite of products. Why is that?

Tableau is wonderful at data visualisation, as is Power BI, of course. However, for enterprise customers, where I’m building a data warehouse, I prefer having analytics closer to the data source, perhaps in a data warehouse or data lake. I like to think about the overall business intelligence architecture. Tableau is superb at data visualisation and it also cleans and integrates data, but to a much lesser extend, which is why they partner so well with Alteryx. I don’t like cleaning data or doing repeatable analytics so close to the end reporting layer and business people seem to want to do it there, without thinking of issues such as robustness, repeat-ability and longevity in the analytical formula that they are creating. I prefer to hand off clean data and analytical formula to the reporting tool as far as possible.

I’m not thinking about Business Intelligence in terms of a spot solution for data visualisation or reporting, for example. I’m looking at the whole canvas. I prefer to clean the data and have it all fixed closer to the source, so that I can get the same number for the same report, regardless of the reporting technology that I use. With Power BI, I can stay within the Microsoft playpen of technologies. I do note however that Tableau Server is in Azure and if you are looking at analytics, that’s another option so that the analytics formula isn’t contained in disparate workbooks. Instead, they are published to Tableau Server and people can should download their workbooks there, for ‘one version of the truth’.

As an external consultant, I work with Power BI because I think it has an astonishing reach technically as well as geographically. Some of my customers are global and I really need the certainty of global resiliency.. Gone are the days when Microsoft had a lot of disparate reporting technologies that didn’t talk to one another very well and we had lots of different interfaces that used to overlap. Customers got really confused about what to use. For example, do you put your KPIs in Analysis Services, or in Reporting Services? Now:

The answer is always Power BI! Take a look:

Microsoft Data Insights Summit

Apart from Data Visualization, what is Power BI useful for?

Power BI is particularly useful for:

  • businesses that are acquiring other businesses and they need somewhere to put the data, and keep the business running in the meantime
  • cost savings
  • GDPR – if you don’t know what this is, you need to contact me to find out more. Microsoft are in the forefront of working with customers to make sure that they are compliant.

Do I still see Tableau?

Yes – some of my customers don’t need public cloud because they pop up their own data centres if and when and where they need them. So, for them, they tend to stick with what they know, and what works for them.

What Business Intelligence tools do I see less of?

I see Qlikview less and less, as customers look to align their reporting and they can replicate their Qlik scripts in SQL Server and SSRS.

I also don’t see Pyramid Analytics appearing much, and I don’t get asked often about them. According to the Gartner report, 2017 may represent a critical period for the company and, rightly or wrongly, the Gartner Magic Quadrant does carry enormous weight when customers are looking for solutions. With many solutions, customers don’t use the full range of features contained in any technical solution, and Pyramid are going to have to work hard to explain how they compare / compete with the Power BI on-premise solution, which is going to go from strength to strength.

However, for others, particularly in the SME market, the Azure offering is extremely compelling. Power BI and Azure together mean that you can focus on the business, rather than working on the technology to support the business. I can also see that more and more data is going into the cloud, and I am part of projects where I am doing exactly that – cloud business intelligence. Cloud Business Intelligence is a real growth offering for me and I plan to keep being ahead of the curve.

Microsoft Data Insights Summit

Are people using Power BI or is it simply good Microsoft Marketing?

People are using it, yes. Here are the numbers, produced by James Phillips during the Power BI Keynote: Microsoft Data Insights Summit

Power BI and the C-Suite

Given it’s reach within the organisation, Power BI can reach the C-suite level as well as the rest of us, in the organisation. Before continuing, it’s probably worth reading about linear vs exponential business growth models e.g. HBR.

 

You can watch the video below, or read on for some of the headlines:

Here are some headlines:

Gross and Net Profit

Net profit

Progress Towards Targets

Revenues and revenue growth rate

Expenses

Employee Engagement

Let’s get started!

Gross and Net Profit

Slide18 Why do CEOs care? As part of the Digital Transformation process, the CEO must develop a guiding philosophy about how he or she can best add value whilst showing ongoing strategic assessment and planning. However, it is difficult for them to allocate time to the collection, cultivation and analysis of data. Instead, they need to focus on strategic decisions, and they need data to run their business, to understand how their customers behave and measure what really matters to the organization. Power BI can help to bring clarity and predictability to the CEO, and this session is aimed at CEOs, and those who support them with data, in order to see how they can be empowered by Power BI, and see it as a key asset within the organisations short and long term future. Slide16

Net Profit

This goes without saying, but keeping an eye on net profit at all times is essential for business leaders. This might be visualized as a line graph or quarterly chart. However you decide to represent the data, it needs to provide detailed, regularly updated information. You can get added value by allowing this data to be broken down.
With Power BI, you’d be able to tap your chart and see real-time data on profits by region, product type or team. First you calculate your gross profit, then your expenses, subtract expenses from gross profit, and you have net profit.

Calculate Gross Profit first:
Gross profit, also called gross margin, shows you how much money you made from selling a product.
It subtracts the selling price from your wholesale cost to calculate the difference. It does not take into account expenses from rent, personnel, supplies, taxes or interest. Gross profit is a required step toward calculating the company’s income or net profit.

Progress Towards Targets

You can use EXPON.DIST function in Microsoft Excel to help measure progress towards your targets.
Use EXPON.DIST to model the time between events, such as how long from the order placement takes to actual delivery. For example, you can use EXPON.DIST to determine the probability that the process takes at most 1 minute.

Revenues and revenue growth rate

By being able to instantly visualize how fast (or otherwise) your business is growing its revenues, it’s much easier to find out what’s going right and what’s going wrong. Need to lose some dead weight? Invest in a growing department? Respond to a new trend among consumers? Tracking your revenues closely is crucial and will help with those decisions. A line graph would again be particularly clear in this instance.

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Think of a Rubik’s cube – people instinctively know how to use them, and to arrange the cube into colors. We also interact with colour and data in the same way; intuitively and quickly.

Expenses

Whether it’s staff, machinery, IT or property, your expenses are one of the biggest drains on your long term success. A dashboard can break these down instantly so you can see where your biggest outgoings are, and then make decisions about what’s costing too much.

Revenue per employee
Revenue per employee is a little like Return on Investment. Are your people actually making enough revenue to justify hiring them? Are they working at 100% capacity or is there room for them to work more, instead of employing new workers? A revenue per employee dashboard helps you make these choices rationally.

Employee Engagement

Measured by an anonymous survey, employee engagement is a key BI factor for any CEO. If your people are motivated, enthusiastic and giving their work 100%, you can be sure your company will grow. By contrast, unengaged colleagues will be a detriment to productivity. It’s essential to keep regular tabs on how employees are feeling about their work.

 

Summary

As part of the Digital Transformation process, the CEO must develop a guiding philosophy about how he or she can best add value whilst showing ongoing strategic assessment and planning. However, it is difficult for them to allocate time to the collection, cultivation and analysis of data. Instead, they need to focus on strategic decisions, and they need data to run their business, to understand how their customers behave and measure what really matters to the organization.
Power BI can help to bring clarity and predictability to the CEO, and this session is aimed at CEOs, and those who support them with data, in order to see how they can be empowered by Power BI, and see it as a key asset within the organisations short and long term future.

Five reasons to be excited about Microsoft Data Insights Summit!

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I’m delighted to be speaking at Microsoft Data Summit! I’m pumped about my session, which focuses on Power BI for the CEO. I’m also super happy to be attending the Microsoft Data Summit for five top reasons (and others, but five is a nice number!). I’m excited about all of the Excel, Power BI, DAX and Data Science goodies. Here are some sample session titles:

Live Data Streaming in Power BI

Data Science for Analysts

What’s new in Excel

Embed R in Power BI

Spreadsheet Management and Compliance (It is a topic that keeps me up at night!)

Book an in-person appointment with a Microsoft expert with the online Schedule Builder. Bring your hard – or easy – questions! In itself, this is a real chance to speak to Microsoft directly and get expert, indepth  help from the team who make the software that you love.

Steven Levitt of Freakonomics is speaking and I’m delighted to hear him again. I’ve heard him present recently and he was very funny whilst also being insightful. I think you’ll enjoy his session. You’ll know him from Freakonomics.

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I’m excited that James Phillips is delivering a keynote! I have had the pleasure of meeting him a few times and I am really excited about where James and the Power BI team have taken Power BI. I’m sure that there will be good things as they steam ahead, so James’ keynote is unmissable!

Alberto Cairo is presenting a keynote! Someone who always makes me sit up a bit straighter when they tweet is Alberto Cairo, and I’m delighted he’s attending. I hope I can get to meet him in person. Whether Alberto is tweeting about data visualisation, design or the world in general, it’s always insightful. I have his latest book and I hope I can ask him to sign it.

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Tons of other great speakers! Now someone I haven’t seen for ages – too long in fact – is Rob Collie. Rob is President of PowerPivotPro and you simply have to hear him speak on the topic. He’s direct in explaining how things work, and you will learn from him. I’m glad to see Marco Russo is speaking and I love his sessions. In fact, at TechEd North America, I only got to see one session because I was so busy with presenting, booth duty etc… but I managed to get to see a session and I made sure it was Marco Russo and Alberto Ferrari’s session.  Chris Webb is also presenting and his sessions are always amazing. I have to credit Chris in part for where I am today, because his blog kept me sane and his generosity during sessions meant that I never felt stupid asking him questions. I’m learning too – always.

Ok, that’s five things but there are plenty more. Why not see for yourself?

Join me at the conference, June 12–13, 2017 in Seattle, WA — and be sure to sign up for your 1:1 session with a Microsoft expert.