Why I wish I’d never backed the Gemini PDA campaign

In December, I had my first experience with Indiegogo, and I backed a campaign to purchase a Gemini PDA. To date, the campaign has generated $2,294,143 which is 284% of target. So there’s plenty of money sloshing around.

As of now, it is May 2018 and despite promises, and a product tracker that seems to be only consistent in its incorrectness, I still do not have my device. This is despite the fact that the Gemini PDA is now available to buy now with delivery mid-June. Initially I was happy to wait until I understood that the device worked but now I’m concerned that I’ve been bypassed. So here’s a lesson in customer service:

In this world where we live in a culture of ‘now’ and constant updates, the silence is disconcerting.

There seems to a precedent where they answer emails reactively when asked about the device. There’s nothing proactive. There is a facility on Indiegogo whereby companies can send updates, but these are coming less and less; only one in May. I’d rather see companies hire a temp or an admin person to look after this and send out proactive emails to update customers. Marketing isn’t difficult and there are plenty of good SaaS offerings for cheap.

I have had no email communication since January when I will get my order; in Indiegogo, it still shows as ‘Order Placed’ which means that it isn’t ready to be shipped yet. I was relying on a Facebook page on when I’d get my device. I’m writing this on 29th May, and this means it is not likely to get here by end of May, which is officially two days away. I feel fobbed off with a Facebook post that said devices would be released, but nothing individual. As a backer, I expect to be treated like an individual; what about people who aren’t on the Facebook page? I expect more communication than this, particularly in this tech-savvy, ‘share everything’ world we live in.

I was an Admin on the Facebook page, but I have taken the decision to remove myself from it. I’ve been as constructive as I can in sending feedback, but my goodwill hasn’t been reciprocated. Now it’s on general release with mid-June date and I still do not have mine. The website says ‘Available now’.
I am disappointed by the lack of communication and I can’t continue to be associated with this situation. Being admin of the Facebook group for Gemini PDA makes me part of it. It feels like I’m endorsing it by continuing to be admin, and I’m absolutely not. People shouldn’t be joining an FB group to get information about their orders, particularly when it involves hundreds of pounds. It’s not a small amount of money. I think I’m being treated in this way because I’m letting them, and I hope that this sends a message back to them regarding customer care and treating backers.
As for my device, if it ever arrives, I’ll probably stick it on eBay, unopened.
It’s not just the poor service that’s made me write this post. I saw a post entitled The Gemini PDA, the Perfect PC for People on Low Incomes? No, no, and no again. Planet haven’t proved themselves worthy yet. Their solution is just out on general release. I was poor – achingly poor – growing up in a rough part of Scotland. Being poor is a hundred thousand humiliations and I have suffered many of those, and I remember what it’s like to be hungry and cold. I still buy second-hand clothes to this day, and I think about every penny. The PDA isn’t cheap. For the poor, being recommended a device which costs hundreds of pounds isn’t going to lift people out of poverty. I lifted myself out of poverty by educating myself, and that meant better access to good libraries, with great facilities and long opening hours. It also helped the loneliness of poverty; you can’t just go and sit in a posh cafe and mingle, for example, so a free reading group where you weren’t expected to part with cash was a great way to spend an evening and certainly better than living in a cold flat. I had this experience and it pains me that the New York Times reported yesterday that libraries have had their funding cut by a third, which is a short-term decision which does not harness the opportunities offered by bringing educational facilities to the poorest.

I don’t believe that Gemini PDAs are a good option for the impoverished, at that price range, and certainly not given the ‘start up’ phase that they are in – if you want to call it that. There can be other, more robust, long-term solutions that are proven and earned trust to help Britain’s vulnerable.

As for me, I’m not sure if I will keep the device or put it, unopened, on eBay. I regret having taken the decision to buy it on Indiegogo and I should probably have got myself an expensive Bluetooth keyboard for my Google Pixel instead. That would really allow me to ‘Type and create on the move.’

 

 

 

Artificial Intelligence Mentoring with Teens in AI

After listening to Satya Nadella’s BUILD keynote this year, I was inspired to do even more with my background in Artificial Intelligence. As a Microsoft Regional Director, I relish in sharing in the positive and forward-looking vision that Microsoft gives because I do think that they are changing the future in many ways.  If you want to see the highlights of Nadella’s keynote, head over to YouTube here for the official Microsoft YouTube channel.

What is Teens In AI? It’s close to my heart because it combines my two loves: technology and diversity. The objective is to increase diversity and inclusion in artificial intelligence.
Teens in AI aims to democratise AI and create pipelines for underrepresented talent through a combination of expert mentoring, talks, workshops, hackathons, accelerators, company tours and networking opportunities that give young people aged 12-18 early exposure to AI for social good. The vision is for AI to be developed by a diverse group of thinkers and doers advancing AI for humanity’s benefit. So…..

I’m excited to be an Artificial Intelligence mentor at @TeensInAI’s Artificial Intelligence Bootcamp & Hackathon.  For more information, visit the Teens in AI website.

There are still places left at the #Hackathon with code ACORNFSM free for kids on free school meals and ACORN80@ gives 80% off – come learn about AI with top industry mentors @MSFTReactor 2-3 June.

I hope to see you there!

Managing activities and productivity as a consultant

I have a hard time keeping track of my activities. It can be hard to track my availability, and my days tend to disappear in a flash. I have tried many different digital ways of doing this, and now I’m going with a mix of digital and analog.

You don’t get what you want, you get what you work for

To lead anyone, you have to have a healthy degree of self-awareness. I find that this is one quality which I don’t see very often, and it’s very hard to try and cultivate it. As a first step, it’s good to measure how you spend your time, because that shows your priorities more clearly, and in a way that you can measure.

I use Trello and Plus for Trello to log my activities over a period of time. The results showed that I spend a lot of time in email, so I worked towards getting it down to Inbox Zero. It took 30 hours of solid email writing to do it, and I did it on planes across the Atlantic to the US, and on planes across to the East. Inbox Zero doesn’t stay for very long though, so I used my last flight to Singapore to try and clear down as many as possible, and I’m down to the last 300 emails. I’m sitting in a cafe in Watford on a Sunday morning, while my dog is being groomed, to clear these down.

My Trello reports showed that I regularly do 15-16 hours of work a day. I work at every available pocket of time, with downtime only for food and for spending time with my son. Sleep gets squeezed. All of this work means that I am leaving a trail of things behind me, and that means it is difficult to unpick when it comes to invoicing and expense time.

Too busy to pick up the $50 notes that you drop as you go

I have hired a Virtual Assistant and she has been helping me a lot; it’s been worth the time investing in training her in my various home-grown systems and I’m hoping to get some time back. I was getting to the point where I was dropping things like expense claims, so, basically, I was dropping $50 dollar notes behind me as I sped along my way. Having the VA onboard means I have someone to help me to pick up the $50 dollars as I go, and it’s worth investing the time.

We are designed to have ideas, not hold them in our heads

I bought the Get Things Done book and something really spoke to me; humans are designed to have ideas, not hold them. That’s true.

I wrote down every single idea that I had. Truthfully, we forget our ideas. I didn’t bother evaluating if it is a good idea or a bad idea; I just wrote it down. I then saw that I could group these ideas, so I start to split them out. One of my headings was ‘Ideas for blog posts’. Very shortly, I had 36 blog post ideas down on the page, which I had collated over the period of a week or so. This is blog post #36. I haven’t lost the other 35; I can pencil them in my planning journal. So let’s dive in and take a look at the system.

Bullet Journalling in a Traveler’s Notebook

I started to use the bullet journal system and I’ve heavily adapted it. It was worth investiging a couple of hours to understand it, and get it set up. Here is the website here. After having tried various electronic and digital systems for the past twenty or so years, this is the only one I’ve found that works for me.

I have a Traveler’s Notebook, which is like a refillable notebook that you can customize yourself. Here’s my Traveler’s Notebook, which I took whilst I was out in the Philippines:

IMG_20180507_184026

The Traveler’s Notebook itself is customizable. I have the following sections:

  • Task List
  • Monthly Tracker with Weekly next to it
  • Daily Tracker
  • Mindsweeper (a brain dump, basically) for blog ideas, things to remember, quotes I like, tentative activities, adresses I need temporarily etc.
  • Slot for holding cards
  • card envelopes for holding things such as train tickets, boarding passes
  • Zippable wallet for holding passport

Here are some ideas to get you going.

Tracking over a Month

I use a monthly spread, which uses a vertical format. On the left hand side, I record anything that is personal. On the right hand side, I record work activities. I don’t split the page evenly, since I have less personal activities than work activities.

Here is my example below. The blue stickers are simply to cover up customer names. I took this shot half-way through my planning session, so you could see the structure before it got confusing with a lot of dates in it.

IMG_20180507_205411

Using my background in data visualization, I try to stick to the data/ink ratio. I am trying to simplify my life and declutter what my brain can take in quickly, so I find that it isn’t necessary to repeat the customer name for every day. Instead, I can just draw a vertical line that has two purposes; to point to a label, and to denote the length of the activity. In other words, it forms a pointer to the label, which shows the customer name. The length of the line covers the number of days that the activity lasts for. So, if the line has the length of four boxes, then this means that the activity lasts for four days.

Occasionally, I’ve got excited because I think I have some free days to book myself out for an unexpected request. Then, I realize it’s because I haven’t marked out the weekends. I work weekends too, and the main reason I mark weekends separately is because my customers don’t work weekends, usually. Therefore, I colour weekends in so that I can easily categorize the days as being part of a weekend or a normal working day. I have also done this for Bank Holidays because I tend to work then, too.

My personal things go on the left, and my work things go on the right.

Tracking over a Week

I put the weeks on the right hand side of the page, and this is where I combine time, tasks and scheduling. I use the grid in order to mark out the days, and, on the same line, I mark out the Task. Then, I can put a tick in the day when I have pencilled in the task itself. You’ll note that I have marked a seven day week. You can see it at the right hand side of the photo.

If I don’t manage to complete an activity that day, I just add another tick mark so the next day so that it gets tracked then.

I don’t eliminate tasks that I haven’t managed to complete that week. Instead, I just put them in the next week instead.

In my weekly list, I don’t cross things off when I’ve done them. I find that it created an unnecessary clutter, and I didn’t want to bring into focus the activities that I’ve done. I’m more interested in what I have to do next. I leave that to my daily list, and I will come onto that next.

Tracking over a Day

For the Day, I use an A6 size notebook, and I use a two-page format. On the left hand side, I go back to the vertical representation of time. This time, the day is chunked in to hours. As before, anything personal or non-work-related goes on the left hand side. On the right hand side, my work activities for the day go here. That may include stand-up meetings, retrospectives or whatever I am doing that day.

I have added in a slot for lunch. I don’t normally take lunch but I need to make sure that I eat something. It is easy for the day to slip by, and I only notice it’s lunchtime because people are not around and the office has gone a bit quieter.

On the right hand side, this forms a mini-brain-dump of activities or thoughts that occur as I proceed throughout the day. It can also form a memo pad of things that I need, such as a phone number, which I jot down before I add to contacts. This usually gets filled during the day. It is a messy space, a place to unload,

Some of these thoughts are important but they are not urgent. I can then clear these items into a less transient mindsweeper but I just need a place to hold them temporarily while I assess their urgency.

The idea of having ideas, rather than holding them in my head, was a revelation to me. I’d been worrying about my memory, and forgetting things. If you forget something, then you lose a part of yourself and you don’t get it back. I set myself memory tests, such as remembering the name of a painting, or a quote of some sorts. When I start to forget things, then I know I am starting to have problems. The reason I started to do this is because I could see the start of someone else’s memory start to go a little, as he forgot things such as who he ate dinner with; simple things like that. It made me very sad, and I realized that our memories make up so much of who are we.

It can be tremendously liberating to divest ourselves of our responsibility of trying to remember everything and to focus on the things that matter. It frees your mind to have more ideas, rather than focus effort on holding ideas, which is harder for your mind to do.

Cloud computing as a leveler and an enabler for Diversity and Inclusion

I had the honour and pleasure of meeting a young person with autism recently who is interested in learning about Azure and wanted some advice on extending his knowledge.
It was a great reminder that we can’t always see people who have conditions such as autism. It also extends to disability, particularly those that you can’t see; examples include epilepsy or even Chronic Fatigue Syndrome.

Diversity gives us the opportunity to become more thoughtful, empathetic human beings.

dyslexia-3014152_1920

Credit: https://pixabay.com/en/users/geralt-9301/

I love cloud because it’s a great leveler for people who want to step into technology. It means that these personal quirks, or differences, or ranges of abilities can be sidestepped since we don’t need to all fit the brogrammer model in order to be great at cloud computing. Since we can do so many things remotely, it means that people can have flexibility to work in ways that suit them.

In my career, I couldn’t lift a piece of Cisco kit to rack it, because I was not strong enough. With cloud, it’s not a problem. The literally heavy lift-and-shift is already done. It really comes down to a willingness to learn and practice. I can also learn in a way that suits me, and that was the main topic of conversation with the autistic youth that I had the pleasure to meet.

I believe that people should be given a chance. Diversity gives us the opportunity to become more thoughtful, empathetic human beings. In this world, there is nothing wrong with wanting more of that humanness.

Dynamic Data Masking in Azure SQL Datawarehouse

I’m leading a project which is using Azure SQL Datawarehouse, and I’m pretty excited to be involved.  I love watching the data take shape, and, for the customer requirements, Azure SQL Datawarehouse is perfect.

secret-3037639_640 Note that my customer details are confidential and that’s why I never give details away such as the customer name and so on. I gain – and retain – my customers based on trust, and, by giving me their data, they are entrusting me with detailed information about their business.

One question they raised was in respect to dynamic data masking, which is present in Azure SQL Database. How does it manifest itself in Azure SQL Datawarehouse? What are the options regarding the management of personally identifiable information?

sasint

As we move ever closer to the implementation of GDPR, more and more people will be asking these questions. With that in mind, I did some research and found there are a number of options, which are listed here. Thank you to the Microsoft people who helped me to come up with some options.

1. Create an Azure SQL Database spoke as part of a hub and spoke architecture.

The Azure SQL Database spoke can create external tables over Azure SQL Datawarehouse tables for moving data into Azure SQL Database to move data into the spoke. One note of warning: It isn’t possible to use DDM over an external table, so the data would have to move into Azure SQL Database.
2. Embed masking logic in views and restrict access.

This is achievable but it is a manual process.
3. Mask the data through the ETL processes creating a second, masked, column.

This depends on the need to query the data. Here, you may need to limit access through stored procs.
On balance, the simplest method overall is to use views to restrict access to certain columns. That said, I an holding a workshop with the customer in the near future in order to see their preferred options. However, I thought that this might help someone else, in the meantime. I hope that you find something that will help you to manage your particular scenario.

How do you know if your org is ready for Data Science? Starting your journey with Azure Databricks

Mentioning  data science at your company may give you an air of expertise, but actually implementing enterprise-wide transformation with data science, artificial intelligence or deep learning is a business-wide transformation activity. It impacts your data and analytics infrastructure, engineering and business interactions, and even your organizational culture. In this post, we will look at a few high-level things to watch out for before you get started, along with a suggestion that you can try Azure Databricks as a great starting point for  your cloud and data science journey.

Note: not all companies are ready for data science. Many of them are still struggling with Excel. This article is meant for you.

So how can you move forward?

1. Have a data amnesty

If you’re still struggling with Excel, then data science and AI can seem pretty far off. Have a data amnesty – ask everyone to identify their key data sources so you can back them up, protect them, and share them better where appropriate.

2. Determine the Data (Im)maturity in your organization.

Take a peep at the following table: where is your organization located?

Democratization of Data

Note: this idea was inspired by Bernard Liautaud

Ideally, you’re headed towards a data democracy, where IT are happy in their guardianship role, and the users have got their data. If this equilibrium isn’t in place, them this could potentially derail your budding data science project. Working on these issues can help your success to be sustainable in the longer-term.

3. All that glitters isn’t data gold

This is the ‘shiny gadget’ syndrome. Don’t get distracted by the shiny stuff. You need your data vegetables before you can have your data candy.

Focus on the business problem you’re trying to solve, not the technology. You will need to think about the success criteria.

You should be using the technology to improve a business process, with clear goals and measurable success. Otherwise it can be disorganized, with a veil of organization that is disguised by the technology.

contacts-3079618_1920

4. Fail to plan, plan to fail

If you fail… that’s ok. You learned ten things you didn’t know before. Next time, plan better, scope better, do better.

How to get started?

Starting in the cloud is a great way to get started. It means that you’re not purchasing a lot of technology and hardware that you don’t need. Abraham Maslow was once quoted as saying “If you only have a hammer, you tend to see every problem as a nail.” Those words are truer than ever as an increasingly complex and interconnected world makes selecting the right tools for the data estate. With that in mind, the remainder of this blog talks about Azure Databricks as a step for data science for the new organization in order to reduce risk, initial outlay and costs.

 

 

What is Microsoft Azure Databricks?

default-open-graphAzure Databricks was designed in collaboration with Microsoft and the creators of Apache Spark. It is designed for easy data science: one-click set up, streamlined workflows and an interactive workspace that enables collaboration between data scientists, data engineers, and business analysts. Each of this roles will have a different style describes how users want to interact with, present, and share information, bearing in mind the varying skillsets of both business users and IT.

So what is Apache Spark? According to Databricks, Apache Spark is the largest open source process in data processing. From the enterprise perspective, Apache Spark has seen rapid adoption by enterprises across a wide range of industries.

So what does Apache Spark give you? Apache Spark is a fast, in-memory data processing engine. For the serious data science organisation, it allows developers to use expressive development APIs to work with data. For information and data workers, they have the ability to execute streaming analytics, longer-term machine learning or SQL workloads – fast. Implemented in Azure, it means that the business users can use Power BI in order to understand their data better.

Apache Spark consists of Spark Core and a set of libraries. The core is the distributed execution engine and the Java, Scala, and Python APIs offer a platform for distributed ETL application development. Spark lets you quickly write applications in Java, Scala, or Python. It comes with a built-in set of over 80 high-level operators. And you can use it interactively to query data within the shell.

The Apache Spark functionality is incorporated in Azure Databricks

In addition to Map and Reduce operations, it supports SQL queries, streaming data, machine learning and graph data processing. Developers can use these capabilities stand-alone or combine them to run in a single data pipeline use case.

It supports in-memory processing to boost the performance of big-data analytic applications, and it works with other Azure data stores such as Azure SQL Data Warehouse, Azure Cosmos DB, Azure Data Lake Store, Azure Blob storage, and Azure Event Hub.

What is so special about Apache Spark, anyway?

For the enterprise and data architects, it can give you the opportunity to have everything in one place: streaming, ML libraries, sophisticated analytics, data visualization. It means that you can streamline in one technological umbrella, but have your data in other data sources such as Azure SQL Data Warehouse, Azure Cosmos DB, Azure Data Lake Store, Azure Blob storage, and Azure Event Hub.

As an architect, I aim to reduce points of failure and points of complexity, so it is the neatness of the final streamlined technology solution that is appealing.

It is also fast, and people want their data fast. Spark enables applications in Hadoop clusters to run up to 100x faster in memory, and 10x faster even when running on disk. Spark makes it possible by reducing number of read/write to disc. It stores this intermediate processing data in-memory. It uses the concept of Resilient Distributed Dataset (RDD), which allows it to transparently store data on memory and persist it to disc only it’s needed. This helps to reduce most of the disc read and write the main time consuming factors of data processing.

 

Data Visualization for the Business User with Azure Databricks as a basis

Azure Databricks brings multi-editable documents for data engineering and data science in real-time. It also enables dashboards with Power BI for accurate, efficient and accessible data visualization across the business.

Azure Databricks is backed by Azure Database and other technologies that enable highly concurrent access, fast performance and geo-replication, along with Azure security mechanisms.

Summary

Implementing enterprise-wide transformation with data science, artificial intelligence or deep learning is a business-wide transformation activity. In this post, there is the suggestion that you can try Azure Databricks as a great starting point for  your cloud and data science journey, with some advice on getting a good ground before you start.

Book Review: Grokking Algorithms: An Illustrated Guide For Programmers and Other Curious People

Grokking Algorithms An Illustrated Guide For Programmers and Other Curious PeopleGrokking Algorithms An Illustrated Guide For Programmers and Other Curious People by Aditya Y. Bhargava

My rating: 5 of 5 stars

I’ve just finished reading the Manning book called Grokking Algorithms An Illustrated Guide For Programmers and Other Curious People

This is a very readable book, with great diagrams and a very visual style. I recommend this book for anyone who wants to understand more about algorithms.
This is an excellent book for the budding data scientist who wants to get past the bittiness of learning pieces of open source or proprietary software here and there, and wants to learn what the algorithms actually mean in practice. It’s fairly easy to get away with looking like a real Data Scientist if you know bits of R or Python, I think, but when someone scratches the surface of that vision, it can become very apparent that the whole theory and deeper understanding can be missing. This book will help people to bridge the gap from learning bits here and there, to learning what the algorithms actually mean in practice.
Recommended. I’m expecting to find that people might ‘pinch’ the diagrams but I’d strongly suggest that they contact the author and credit appropriately.
I’d recommend this book, for sure. Enjoy!

View all my reviews