Category Archives: Speaking Events

Join me at Live! 360 Orlando to learn more about Applied Business Analytics

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I’m delighted to be speaking at Live! 360 Orlando and I’m presenting a workshop on From Business Intelligence to Business Analytics with the Microsoft Data Platform. The conference is held on November 17-22, 2019 at the Royal Pacific Resort at Universal Orlando in Florida.

Data becomes relevant for decision making when we start to use it properly, so this workshop will demonstrate the use of analytics for real-life use cases. This means that you can make use of the knowledge you learn from the session when you go back to the office. In this workshop, we will make analytics relevant to your business so your organization will feel the benefit. If you’d like to register, please click here to register and please use code SPKLIVE87 and receive $400 off the standard pricing for both the 6-Day and 5-Day Packages.

Here are the topics we’ll cover:

  • Introduction to Analytics with the Microsoft Data Platform
  • Essential Business Statistics for Analytics Success – the important statistics that business users use often in business spheres, such as marketing and strategy.
  • Business Analytics for your CEO – what information does your CEO really care about, and how can you produce the analytics that she really wants? In this session, we will go through common calculations and discuss how these can be used for business strategy, along with their interpretation.
  • Analytics for Marketing – what numbers do they need, why, and what do they say? In this session, we will look at common marketing scenarios for analytics, and how they can be implemented with the Microsoft Data Platform.
  • Analytics for Sales – what numbers do they need on a sales dashboard, why, and what do they say? In this session, we will look at common sales scenarios for analytics such as forecasting and ‘what if’ scenarios, and how they can be implemented with the Microsoft Data Platform.
  • Analytics with Python – When you really have difficult data to crunch, Python is your secret Power tool.
  • Business Analytics with Big Data – let’s look at Big Data sources and how we can do Big Data Analytics with tools in Microsoft’s Data Platform.

Power BI and Marketing Data

What kind of applicable analytics will we cover? One important area in data is marketing. The primary aim of a Digital Marketing Analytics Report is to provide Digital Marketing Managers, Product Owners, and other relevant teams and stakeholders with a clear and easily-usable overview of the KPIs related to their campaigns. They should be designed in such a way that whoever is looking at them can interact with them in an easy, productive way. A Digital Marketing Analytics Report will generally have a wide range of visuals, of different levels of complexity, that display data in different ways.

The average attention span is only eight seconds. Therefore, it makes perfect sense to gather your data onto one canvas in a visually-compelling way, rather than relying on a lengthy PowerPoint or a cluttered Excel spreadsheet. Power BI is a hugely effective way of gathering and connecting to various data sources and using them to create a more engaging experience. 

When it comes to marketing specifically, there are some major advantages that come with processing your data in Power BI. Visualizing your data in a Power BI report lets you recognise patterns and trends that might have otherwise gone unnoticed if the data was in a text-based format. It is also an effective way to identify and create your company’s own best practices vs the common best practices of the industry; you can estimate traffic by creating a click-through-rate curve for your site, rather than just using the industry average.

Power BI can also make it easier to answer the questions that your clients and other stakeholders ask of you. Being able to explore and interact with live data means that, when you’re asked a question, rather than responding by saying “I don’t know, but I’ll get back to you” you can say “Let’s find out”. Not only does this mean that your client doesn’t have to wait for an answer, but it means that you are showing that you’re being honest and transparent about your data and how you analyse it.

You can also interact with your data in other ways — for example, it’s easy to isolate data from a specific time period in one visualization, and have this be reflected in the other visualizations on the Dashboard. You could select the spendings from a particular week, and have the KPIs from this week be highlighted, allowing you to better see the relationship between these two statistics.

Colour can also be used in a Dashboard to have certain effects, such as showcasing relationships clearly and drawing attention to the most important data, either overall or during user interaction. Colour can also be used to illustrate performance — for example, green statistics to represent above target, yellow for on target, and red for below target.

You can use a Power BI Dashboard to give an overview of impressions, campaign clicks, and average spend for a digital campaign. These statistics combined gives an overview of the effectiveness of and costs related to the campaign — seeing these statistics side by side can give a better idea of how they relate to each other.

Marketers are already learning how to use better tools for bigger datasets, and the environment is quickly evolving. Digital marketers working in eCommerce are experiencing over 45% increases year-on-year (1). People are becoming more digitally literate, and are learning how to search more effectively across more devices — often even beginning a purchase on one device and completing it on a different one. There are more search engines, more sites, and overall more options for users, and many users are responding to this by becoming better, more specific searchers. This means that, as marketers, instead of worrying about 1,000 keywords, you need to worry about 1,000,000. You need to have a much better idea of your marketing initiatives, click-throughs and engagements, and you need to convey this in a way that will be both understandable and engaging. 

If there are larger initiatives or recurring marketing programs that you need to track, it may be beneficial to setup specific reports, but in general, a Power BI dashboard is a great way to share your insights in a way that doesn’t end at a basic display of your data, but allows the data to be further investigated on-the-spot and when needed.

Join me in Live! 360 Orlando to learn more about Power BI and marketing, along with other topics.

DataPlatformSummit: Delighted to be returning to present on #AI and #PowerBI in India!

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I am delighted to be presenting at Data Platform Summit 2019 in Bengaluru, India in August 2019!

What is Data Platform Summit? The conference packs a punch of learning and information, and you will get actionable knowledge that you and your company can benefit from – right away! The conference is a well-put together plan of 3 Days of Pre-Conference Training , 3 Days of Conference Learning, 7 Key Technology Tracks, 50+ Global Subject Matter Experts & Industry leaders, 100+ Sessions, 300+ Companies, 1000+ Attendees, 90+ Subjects, 30+ Technologies & an unimaginable flow of intelligence & expertise from friends and colleagues in the industry from around the world.

My sessions are listed here and I am going to fast-track attendees to be empowered to start their company’s journey in Artificial Intelligence and related technologies such as Power BI. The conference covers everything from ingesting data to DevOps, so there is something for everyone and every business to be successful.

Register here before it is too late!

4_dps2019_Speakers

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

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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?

 

Want to learn how to skill up from #BusinessIntelligence to #ArtificialIntelligence? Join me at #Live360 in Florida

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I’ll be speaking at Live! 360 Orlando, December 2-7. Surrounded by your fellow industry professionals, Live! 360 provides you with immediately usable training and education that will keep you relevant in the workforce.

SPECIAL OFFER: As a speaker, I can extend $500 savings on the 5-day package. Register here: http://bit.ly/OSPK88Reg

OSPK88

Workshop: Moving from BI to AI: Artificial Intelligence Skills for Business Intelligence Professionals

Are you interested in reusing your existing BI skillset in order to add Artificial Intelligence to your skillset? Is your organisation interested in applying AI at a practical level? If so, this precon is for you.

In this precon, you will leverage your existing BI skillset to learn Microsoft’s latest AI technologies. You will learn AzureML, using your existing SSIS expertise. You will also learn R and Python, using your knowledge of SQL in SQL Server to get a working knowledge of these languages and their use in AI. You will use your conceptual knowledge of Business Intelligence to learn how to choose the right model for your AI work, and how to identify its value and validity.

Join this session to add AI to your organization’s technical capability, springboarding from skills that you already possess.

Workshop Agenda

Moving from BI to AI: Artificial Intelligence skills for Business Intelligence professionals

9.00am AI for the Enterprise

AI for the Enterprise

What is AI? Terminology that you need to know

Blueprint for AI in the Enterprise

Technology Overview; how do you choose the best tools to provide business value?

 

In this section, we will look at what you need to know to set the scene for AI for the enterprise. There is a very wide range of technologies in the AI space, and this section will introduce the key players and how they compare with one another, along with clear explanations on how they are used best. The session will also propose a blueprint for delivering successful AI projects, from the business perspective.

 

10.00am Get started with AI in Azure

  • Introduction to AzureML
  • Build simple machine learning models with Azure Machine Learning

In this section, you will get hands-on experience in practice building a machine learning model from end-to-end, using AzureML. This is intended to formalize some of the knowledge you have learned so far. In this section, you will ingest data, select a model, train and test a model, and make it production-ready. Then, you can visualize your results in Power BI.

11.30 Selecting your model in AI

An exploration of models in AI

Selecting models in AI

Evaluating models in AI

In this section, we will cover AI models in detail. We will look at the models themselves, their differences and similarities, and how to choose between the models. We will also look at ways of evaluating models.

12.30 – 1.30 Lunch

1.30 Working with Microsoft ML Server and R

  • Fundamentals of R
  • Microsoft ML Server
  • Using R with Microsoft ML Server

In this section, we will cover the fundamentals of R, and how we can use it to create robust, production models using Microsoft ML Server. R is a first class citizen in Microsoft’s Data Platform offerings, and it touches other technologies, such as AzureML, SQL Server and Power BI. We will cover its use in Microsoft Machine Learning Server to help provision a flexible enterprise platform for analyzing data at scale, building intelligent apps, and discovering valuable insights across your business. Machine Learning Server meets the needs of all constituents of the process – from data engineers and data scientists to line-of-business programmers and IT professionals. It offers a choice of languages and features algorithmic innovation that brings the best of open-source and proprietary worlds together.

2.45 Break

3.00 Python Data Science Notebook and Labs

Python is an important skill in analysing data, data science and artificial intelligence. In the final segment, you will learn about Python, how to use it, and how to use Notebooks to work with your code.

5.00 Wrap up and QA

Get Hygge with it – Your 5 Step Guide to #ESPC18

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ESPC18-Speaker-Graphic-Jennifer

I’m excited to be presenting at the European Sharepoint, Office365 and Azure Conference in Copenhagen on 26th – 29th November. The conference has great content delivered by Microsoft MVPs, Regional Directors and Microsoft team members. It’s a great place to get all of your Microsoft content and news to help you with your current technical estates, as well as plan for the future. I’d recommend attending since it is THE European conference for these topics and there are thousands of attendees going along to learn, so why aren’t you?

BOOK YOUR TICKET today and use coupon code ESPC18SPK to receive a €100 discount.

I’m delighted to be giving the Artificial Intelligence keynote: Artificial Intelligence: Winning the Red Queen’s Race.

To help you to navigate the conference, here’s a set of handy tips. I hope to see you there!

PLAN Your Sessions

Explore the ESPC18 SCHEDULE to identify what sessions you’d like to attend. Create your own schedule suited to you. If you are travelling with colleagues, divide and conquer by  attending different sessions. Afterwards swap notes to increase your learning.
Don’t have time to delve through our 120+ conference schedule? We have created dedicated pages to save you time. Check out the ESPC conference schedule based on IT PRO, DEV, BDM, AZURE or MICROSOFT SESSIONS.

CONNECT with Your Peers

Join the ESPC18 App (Login details announced in the coming weeks) & follow the hashtag #ESPC18 to find out whose attending. Why not make your presence known by sending out a tweet introducing yourself. Arrange to meet new individuals at ESPC – you never know what you might discover! Helpful tip: Carry some business cards with you to share with the new people you meet.

LEARN, Learn, Learn

Before arriving at ESPC, take some time to identify what questions you want answered. Prepare them advance to ask during a session Q&A. Why not take a break from sessions and advance your skills at the ESPC labs or check out the Ask the Experts session. Remember, it’s good practice to note three important key takeaways from each session.

Have Fun

With 2,000 delegates expected to attend, ESPC offers a host of exciting day and night experiences. Check out the WOMEN IN TECHNOLOGY LUNCH, a jam packed EXPO HALL or challenge other delegates and the ESPC team to some fun games in the Community Area.
Not enough? Be sure to join the EXPO drinks on Tuesday evening or enjoy a magical night at the sell-out ESPC18 PARTY: A NIGHT AT THE CIRCUS.

SHARE with your Team

Schedule a meeting post conference to share your key learnings with your fellow co-workers. Impress colleagues with your advanced knowledge while maximizing value for your company. Share your inspiration and make plans to implement what you learned.

Still undecided about attending The leading European SharePoint, Office 365 & Azure Conference? Visit 10 REASONS TO ATTEND ESPC18 to see why you need to be there.

BOOK YOUR TICKET today and use coupon code ESPC18SPK to receive a €100 discount.

Microsoft Ignite interview with Kevin Farlee on Azure SQL Database Hyperscale

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Azure SQL Database is introducing two new features to cost-effectively migrate workloads to the cloud. SQL Database Hyperscale for single databases, available in preview, is a highly scalable service tier that adapts on demand to workload needs. It auto-scales up to 100 TB per database to significantly expand potential for app growth.
What does this mean? It’s one of the most fundamental changes to SQL Server storage since 7pm. So this is big: big news, and very big data stores. I am very lucky because I got to interviewe Kevin Farlee of the SQL Server team about the latest news, and you can find the video below.

I am sorry about the sound quality and I have blogged so that the message is clear. When I find the Ignite sessions published, I will add in a link as well.
What problem are the SQL Server team solving, with Hyperscale? The fundamental problem is how do you deal with very large databases in the cloud. VLDBs is the problems that people want to do with normal operations. All the problems with VLDBs occur due to the sheer size of data, such as backups, restores, maintenance operations, scaling. Sometimes these can take days to conduct these activities, and the business will not wait for these downtimes.  If you are talking tens of terabytes, that takes day and ultimately Microsoft needed a new way to protect data and VLDBs. The SQL Team did something really smart and rethought very creatively on how they do storage, in order to take care of the issues with VLDBs in the cloud.
So, the Azure SQL Server team did something that is completely in line with one of the main benefits and key features of cloud architecture: they split out the storage engine from the relational engine. Storage implementation was completely rethought and remastered from the ground up. They took the viewpoint over how you would go about architecting, designing and building for these solutions in the cloud, if you were to start from scratch?
The Azure SQL Server database team did a smart thing: Azure SQL Server is using microservices to handle VLDBs.
The compute engine is one microservice which is taking care of it’s role, and then another microservice that is taking care of the logging, and then a series of microservices that handle data. These are called page servers, and they interface at the page level. The page servers host and maintain the data files. Each page server handles about a terabyte of data pages. You can add on as many as you need.
Ultimately, compute and storage are decoupled so you can scale compute without moving the data. This means it’s possible to keep adding more and more data, and it also means that you don’t have to deal with the movement of data. Moving data around when there are terabytes and terabytes of data isn’t a trivial task. The page servers have about a terabyte of data each, and the page servers have about a terabyte’s worth of SSD cache.
The ultimate storage is Azure Blob Storage, because blob storage is multiply redundant and it has features like snapshots, so this means that they can do simultaneous backups by just doing a snapshot across all of the blobs. This has no impact on workload.
Restores
Restores are just instantiating a new set of writeable disks from a set of snapshots, and works with the the page servers and the compute engine to take care of it, working in symphony. Since you’re not moving the data, it is faster.
I’m personally very impressed with the work that the team they’ve done, and I’d like to thank Kevin Farlee for his time. Kevin explains things exceptionally well.
It’s worth watching the video to understand it. As well as the video here, Kevin goes into detail in his Microsoft Ignite sessions, and I will publish more links when I have them.
Community
One advantage in doing the MIcrosoft Community Reporter role is that I get to learn from the experts, and I enjoyed learning from Kevin throughout the video.
It seems to me that the Azure SQL database team have really heard the voice of their technical audience and they’ve worked passionately and hard to tackle these real life issues. I don’t know if it is always very clear that Microsoft is listening but I wanted to blog about it, since I can see how much the teams take on board the technical ‘voice’ from the people who care about their solutions, and who care enough to share their opinions and thoughts so that Microsoft can improve their solutions.
From the Azure architecture perspective, it works perfectly with the cloud computing concept of decoupling the compute and the storage. I love watching the data story unfold for Azure and I’m excited by this news.

Microsoft Ignite interview with Executive Team on #ArtificialIntelligence, #Data, #OpenSource and #Cloud

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There were a number of announcements across Azure Data + AI at Microsoft Ignite, and Im delighted to say that I had the opportunity to interview Rohan Kumar, Corporate Vice President, Azure Data at Microsoft, and Eric Boyd, Corporate Vice President, AI at Microsoft.

In the interview, Rohan Kumar and Eric Boyd give their opinions and thoughts to myself and Cathrine Wilhelmsen on the big picture across Data & AI.  I was super excited since it was the first time that these Microsoft executives had been interviewed together and I was particularly interested to see how Rohan and Eric cross-reference each other’s areas. It’s clear that they are working in orchestration as a team, and I’m glad to see that because I do see that data and Artificial Intelligence impact one another so much.

Rohan and Eric talk about the announcements that excited them both, and there was also a good discussion on the role of Open Source at Microsoft, and what role it plays in Microsoft’s Data and Artificial Intelligence story.

There was a great discussion on Eric and Rohan’s thoughts on its role in making insights, Artificial Intelligence and insight-driven analysis real for organizations. Every organization on the planet has got data, and Microsoft are carving a path for the organizations that want to make use of it.

I’m personally interested in Amara’s Law, which states that “We tend to overestimate the effect of a technology in the short run and underestimate the effect in the long run.” So I was interested in Rohan and Eric’s perspectives on what aspects of AI are real versus hype. What is Microsoft doing to make AI real and actionable for customers?

amara

We wrapped up with a great conversation on the Microsoft and Facebook collaboration?, which I personally find interesting.

It was  real life-achievement for me to participate in the Microsoft Ignite Community Reporter team, and it was a real achievement for me to interview the Microsoft Executives. I’d like to thank Rohan Kumar and Eric Boyd for their time and for sharing their wisdom and insights.

I was also glad to be on board with Cathrine Wilhelmsen. Cathrine was a wonderful friend and support throughout the week and she’s not just an expert in her domain, but she’s a very giving person in terms of her friendship and support. So the interview holds special meaning for me since I was glad to have the opportunity to work with her.