A seamless AI solution providing a scalable, cost effective and enhanced customer service experience in the area of intranet content navigation.
See our case study here: exposé case study – Local Government – Virtual Customer Assistant Chatbot
A seamless AI solution providing a scalable, cost effective and enhanced customer service experience in the area of intranet content navigation.
See our case study here: exposé case study – Local Government – Virtual Customer Assistant Chatbot
We increasingly hear statements like, “machines are smarter than us” and “they will take over our jobs”. The fact of the matter is that computers can simply compute faster, and more accurately than humans can. So, in the short video below, we instead focus on how machines can be used to assist us do our jobs better, rather than viewing AI as an imminent threat. It shows how AI can assist in better occupational health and safety in the hospitality industry. It does however apply to many use cases across many industries, and positions AI as an enabler. Also see an extended description of the solution after the video demo.
With the introduction of video, image and video streaming analytics, the realm of advanced data analytics and artificial intelligence just stepped up a notch.
All the big players are currently competing to provide the best and most powerful versions; Microsoft with Azure Cognitive Services APIs, Amazon with AWS Rekognition, Google Cloud Video Intelligence as well as IBM with Intelligent Video Analytics.
Not only can we analyse textual or numerical data historically or in real time, we’re now able to extend this to use cases of videos and images. Currently, there are API’s available to carry out these conceptual tasks:
o Identify a person from a repository / collection of faces
o Celebrity recognition
o Identify emotion, age, and other demographics within individual faces
o Return objects the algorithm has identified within specific frames i.e. cars, hats, animals
o Return location settings i.e. kitchen, beach, mountain
o Return activities from video frame i.e. riding, cycling, swimming
o Track movement/path of people within a video
o Auto moderate inappropriate content i.e. Adult only content
o Recognise text from images
Thanks to cloud computing, this complex and resource demanding functionality can be used with relative ease by businesses. Instead of having to develop complex systems and processes to accomplish such tasks, a business can now leverage the intelligence and immense processing power of cloud products, freeing them up to focus on how best to apply the output.
In a nutshell, vendors offering video and image services are essentially providing users API’s which can interact with the several located cloud hosts they maintain globally. All the user needs to do, therefore, is provide the input and manage the responses provided by the many calls that can be made using the provided API’s. The exposé team currently have the required skills and capability to ‘plug and play’ with these API’s with many use cases already outlined.
As capable as these functions already are, improvements are happening all the time. While the potential scope is staggering, the following cases are based on the currently available. There are potentially many, many more – the sky really is the limit.
This is a camera used to view a person’s face, which then gets integrated with the facial recognition API’s. This then sends a response, which can be used to either open the entry or leave it shut. Not only does this improve security, preventing the use of someone else’s card, or pin number, but if someone were to follow another person through the entry, security can be immediately alerted. Additional cameras can be placed throughout the secure location to ensure that only authorised people are within the specified area.
As an extension of the above cardless, pinless entry using facial recognition only use case, additional API’s can be used to not only determine if a person is authorised to enter a secure area, but to check if they are wearing the correct safety equipment. The value this brings to various occupational health and safety functions is evident.
We have performed the following scenario ourselves, using a selection of API’s to provide the alert. The video above demonstrates a chef who the API recognises using face detection. Another API is then used to determine that he is wearing the required head wear (a chef’s hat). As soon as the chef is seen in the kitchen not wearing the appropriate attire, an alert is sent to his manager to report the incident.
To provide some understanding of how this scenario plays out architecturally, here is the conceptual architecture used in the solution showcased in the referenced Video.
· Face Repository / Collection
Images of faces of people in the organisation. The vendors solution maps facial features, e.g. distance between eyes, and stores this information against a specific face. This is required by the succeeding video analytics as it needs to be able to recognise a face from various angles, distances and scenes. Associated with the faces are other metadata such as name, date range for permission to be on site, and even extra information such as work hours.
Architecture of the AI Process:
· Video or Images storage
Store the video to be processed within the vendors storage location within the cloud, so it is accessible to the API’s that will be subsequently used to analyse the video/image.
· Face Detection and Recognition API’s
Run the video/images through the Face Detection and Recognition API to determine where a face is detected and if a particular face is matched from the Face Repository / Collection. This will return the timestamp and bounding box of the identified faces as output.
· Frame splitting
Use the face detection output and 3rd party video library to extract the relevant frames from the video to be sent off to additional API’s for further analysis. Within each frames timestamp create a subset of images from the detected faces bounding box, there could be 1 or more faces detected in a frame. The bounding box extract will be expanded to encompass the face and area above the head ready for the next step.
· Object Detection API’s
Run object detection over the extracted subset of images from the frame. In our scenario we’re looking to detect if the person is wearing their required kitchen attire (Chef hat) or not. We can use this output in combination with the person detected to send an appropriate alert.
· Messaging Service
Once it has been detected that a person is not wearing the appropriate attire within the kitchen an alert mechanism can be triggered to send to management or other persons via e-mail, SMS or other mediums. In our video we have received an alert via SMS on the managers phone.
Below we have highlighted the components of the Architecture in a diagram:
These are just a couple of examples of how we can interact with such powerful functionality; all available in the cloud. It really does open the door to a plethora of different ways we can interact with videos and images and automate responses. Moreover, it’s an illustration of how we can analyse what is occurring in our data, extracted from a new medium – which adds an exciting new dynamic!
Video and image analytics opens up immense possibilities to not only further analyse but to automate tasks within your organisation. Leveraging this capability, the exposé team can apply our experience to your organisation, enabling you to harness some of the most advanced cloud services being produced by the big vendors. As we mentioned earlier, this is a space that will only continue to evolve and improve with more possibilities in the near future.
Do not hesitate to call us to see how we may be able to help.
Contributors to this solution and blog entry:
Jake Deed – https://www.linkedin.com/in/jakedeed/
Cameron Wells – https://www.linkedin.com/in/camerongwells/
Etienne Oosthuysen – https://www.linkedin.com/in/etienneo/
Chris Antonello – https://www.linkedin.com/in/christopher-antonello-51a0b592/
Let Eddie, our tester, take you through a quick test drive of Tableau’s new data prep tool called Tabeau Prep. He also calls out the pros and the cons.
Also read the more in depth article here.
Exposé designed and developed a solution that uncovered whether there were strong relationships between known characteristics of branches and their success in order to determine new locations to be considered and the services they will offer.
See our case study here: exposé case study – Agribusiness – Branch locations and success criteria using predictive analytics
GDPR (General Data Protection Rules) is the European privacy and data protection law that comes into effect on the 25th of May 2018. This surely doesn’t affect Australian companies, right? Wrong!
The thing is, whilst the new regulation governs data protection and privacy for all EU citizens it also addresses personal data outside of the EU. The impact will be far-reaching, including Australian businesses, as all businesses concerned with the gathering and analysis of consumer data could be affected.
According to the Office of the Australian Information Commissioner (OAIC), Australian businesses of any size may need to comply. In addition, all Australian businesses must comply with the Australian Privacy Act 1988.
Are these two laws complimentary? Some of the common requirements that businesses must adhere to include:
But some GDPR requirements are not part of the Australian Privacy Act, such as the “right to be forgotten”.
We would suggest that Australian businesses firstly establish whether they need to comply with GDPR. If they do, then they should take prompt steps to ensure their data practices comply. Businesses should already comply with the Australian Privacy Act, but also consider rolling out additional measures required under GDPR which are not inconsistent with the Privacy Act.
In a nutshell, the GDPR applies to any data processing activities undertaken by an Australian business of any size that:
Refer to the following link for more information: https://www.oaic.gov.au/media-and-speeches/news/general-data-protection-regulation-guidance-for-australian-businesses
Once a need for your organisation to comply has been established, it is worth ascertaining whether the actual tools you are using for analytics comply; specifically regarding the last bullet point above (tracking and analysing individuals).
In the next section of this article we look at two common players in the analytics space; Power BI and Qlik, through the lens of GDPR (and by default the Australian Privacy Act).
The scope of GDPR is intended to apply to the processing of personal data irrespective of the technology used. Because Power BI and Qlik may be used to process personal data, there are certain requirements within the GDPR that compel users of these technologies to pay close attention:
Power BI can be viewed through the lens of GDPR (and the Australian Privacy Act for that matter) via four pillars in the Microsoft Trust Centre. With specific reference to GDPR, Microsoft states, “We’ve spent a lot of time with GDPR and like to think we’ve been thoughtful about its intent and meaning”. Microsoft released a whitepaper to provide the reader with some basic understanding of the GDPR and how it relates to Power BI. But meeting GDPR compliance will likely include a variety of different tools, approaches, and requirements.
Power BI is built using the “Security Development Lifecycle”, Through Azure Active Directory Power BI is protected from unauthorised access by simplifying the management of users and groups, which enables you to assign and revoke privileges easily.
The Microsoft Trust Centre clearly states that “you are the owner of your data” and it is not used for mining for advertising. http://servicetrust.microsoft.com/ViewPage/TrustDocuments?command=Download&downloadType=Document&downloadId=5bd4c466-277b-4726-b9e0-f816ac12872d&docTab=6d000410-c9e9-11e7-9a91-892aae8839ad_FAQ_and_White_Papers
From the Power BI white paper, “We use your data only for purposes that are consistent with providing the services to which you subscribe. If a government approaches us for access to your data, we redirect the inquiry to you, the customer, whenever possible. We have challenged, and will challenge in court, any invalid legal demand that prohibits disclosure of a government request for customer data.” https://powerbi.microsoft.com/en-us/blog/power-bi-gdpr-whitepaper-is-now-available/
Microsoft complies with leading data protection and privacy laws applicable to Cloud services, and this is verified by third parties.
Microsoft provides clear explanations on:
The BI vendor, Qlik, released a statement that declares “With more stringent rules and significant penalties, GDPR compels businesses to use trusted vendors. Qlik is committed to our compliance responsibilities – within our organization and in delivering products and services that empower our customers and partners in their compliance efforts.” – https://www.qlik.com/us/gdpr
Qlik released an FAQ document as a GDPR compliant vendor stating that they have various measures in place to protect personal data and comply with data protection/privacy laws, including GDPR:
For more information, please view the links below:
The two vendors discussed are clear in their commitment to ensuring their security arrangements can comply with GDPR. This does not mean that other major players (Tableau, Google, etc.) do not have the same initiatives in flight, we have only focused on Microsoft and Qlik.
Whilst there is no ‘magic button’ available to ensure all regulations are miraculously met, it is possible regardless of vendor:
GDPR can indeed be a tricky landscape to navigate – if in doubt, check it out.
We can certainly assist in guiding you through the process from an Data and Analytics perspective.
Power BI has truly evolved over the past few years. From an add-on in Excel to a true organisation wide BI platform, capable of scaling to meet the demands of large organisations; both in terms of data volumes and the number of users. Power BI now has multiple flavors and a much more complicated licencing model. So, in this article, we demystify this complexity by describing each flavor of Power BI and their associated pricing. We summaries it all at the end with some scenarios and in a single cheat sheet for you to use.
I thought it best to separate the “why” (i.e. why do you use Power BI – Development or Consumption), the “what” (i.e. what can you do given your licence variant), and the “how much” (i.e. how much is it going to cost you) as combining these concepts often leads to confusion as there isn’t necessarily an easy map of why what and how much.
“Why” deals with the workload performed with Power BI based on its deployment – I.e. why do you use Power BI? Is it for Development or for Consumption. This is very much related to the deployment platform (i.e. Desktop, Cloud, On-Premise or Embedded).
The term “consumption” for the purpose of this article could range from a narrow meaning (I.e. the consumption of Power BI content only) to a broad meaning (i.e. consumption of-, collaboration over-, and management of Power BI content – I refer to this as “self-serve creators”).
In the table above, I not only dealt with the “why”, but I also introduced the variants of Power BI; namely Desktop, Free, Pro, On-Premise and Embedded. Variants are related to the licence under which the user operates and it determines what a user can do.
Confused? Stay with me…all will become clearer.
The Power BI journey (mostly) starts with development in Desktop, then proceeds to a deployed environment where it is consumed (with or without self-serve). Let’s close the loop on understanding the flavours of Power BI by looking at what this means from a licencing cost perspective.
Disclaimer: The pricing supplied in the following table is based on US-, Australian-, New Zealand- and Hong Kong Dollars. These $ values are by no means quotes but merely taken from the various calculators and pricing references supplied by Microsoft as at the date of first publication of this article.
**Other ways to embed Power BI content are via Rest API’s (authenticated), SharePoint online (via Pro licencing) and Publish to Web (unauthenticated), but that is a level of detail for another day. For the purpose of this article, we focus on Power BI Embedded as the only embedded option.
Even if you deploy to the Cloud and intend to make content available to pure consumers of the content only (non-self-serve users), whether it be in PowerBi.com or as embedded visuals, you will still need at least one Pro licence to manage your content. The more visual content creators (self-server creators) you have, the more Pro licences you will need. But, it is worth considering the mix between Pro and Premium licences, as both Pro and Premium users can consume shared content, but only Pro users can create shared content (via self-service), so the mix must be determined by a cost vs capacity ratio (as discussed below).
Premium allows users to consume shared content only. It does not allow for any self-service capabilities. Premium licences are not per user, but instead, based according to planned capacity, so you pay for a dedicated node to serve your users. Consider Premium licencing for organisations with large numbers of consumers (non-self-serve) that also require the dedicated computer to handle capacity. The organisation would still require one or more Pro licences for content management and any self-serve workload.
Premium licencing is scaled as Premium 1, 2 or 3 dependant on the number of users and required capacity. You can scale up your capacity by adding more nodes as P1, P2 or P3, or scale up from P1 to P2, and from P2 to P3.
Given that Pro users can do more than Premium users, and given that you will need to buy one or more Pro licences anyway, why would you not only use Pro rather than Premium? There are two reasons:
The diagram below shows the user and capacity tipping points (discussed further in scenario 1 below):
Right, you now understand the “why”, “what” and “how much” – let’s put it all together through examples (I will use Australian $ only for illustrative purposes). Please note that there are various ways to achieve the scenarios below and this is not a comprehensive discussion of all the options.
A large organisation has 10 Power BI Developers; their Power BI rollout planning suggest that they will grow to 50 self-service creators and 1450 additional high activity consumers in 12 months. And that they will grow to 125 self-serve creators and 5000 high activity consumers in 48 months:
10 x Power BI Desktop licences = $0 x 10 = $0
500 x Power BI Pro licences to cover both self-serve users and consumers = $12.70 x 500 = $6,350
Total – A$6,350.00pm
50 x Power BI Pro licences to cover self-serve users = $12.70 x 50 = $635
1 x P1 node to cover the next tranche of high activity consumers = $6,350
Total – A$6,985.00pm
Add Power BI Pro licences as required up to their planned 125 = $12.70 x 125 = $1,588
Add 1 additional P1 node at 1,450 users, and again at 2,900 users, and again at 4,250 users = $25,400 for 4 x P1 nodes
Total after 4 years at 5000 high activity consumers and 125 self-serve creators – A$26,988.00pm
A small organisation with 1 Power BI developer, 5 additional self-service creators and 10 additional consumers of visual content, with no custom applications/ websites.
1 x Free version of Power BI Desktop: 1 x $0
15 x Pro licences as both visual creators and mere consumers will take part in shared content: 15 x $12.70
Total – A$190.50pm
A small ISV organisation with 3 Power BI developers want to embed Power BI content in an application that they sell. The application must be up 24 x 7 and do not require a very high volume of concurrent users, but licencing cannot be on a per-user basis.
3 x Free version of Power BI Desktop: 3 x $0
1 x Pro licences acting as the mater of the Shared content: 1 x $12.70
A1 Node pricing: 1 x $937
Total – A$950.00pm
A medium sized organisation with 5 Power BI developers want to embed Power BI content in an internal portal such as SharePoint which is used by potentially 250 users. They also have 10 self-service creators and 25 consumers of Power BI content through the Power BI portal.
5 x Free version of Power BI Desktop: 3 x $0
26 x Pro licences acting as 1 mater of the Shared content and 25 consumers: 26 x $330.20
A1 Node pricing: 1 x $937
Total – A$1,267.20pm
Any process is shown in Australian $
Disclaimer: The pricing supplied in the following table are by no means quotes, but merely taken from the various calculators and pricing references supplied by Microsoft as at the date of first publication of this article.
Exposé designed and developed a solution that saw an increasingly temperamental Networks Asset Analytical solution move to the Exposé developed Enterprise Analytics Platform.
• Allows staff to focus on business-critical tasks by utilising the data created by the system.
• Reduces support costs due to the improved system stability.
• Utilises the IT resources for other projects that improve business productivity.
This case study shows how we replaced a global pipeline prediction system with a predictive solution based on Azure Machine Learning. Water consumption demand prediction is now highly accurate and it provides a much higher degree of flexibility and cost savings to SA Water.
A Blockchain, in its simplest form, is a distributed database system where there is no one master (primary) database, but many databases that are all considered primary. All parties participate in populating entries into the respective databases and receive the entries of the other participants.
But how does this apply to your business, and is this profoundly going to change how the world works? Let’s look at an analogy: Imagine I create a song and generate a file of my recording in mp3 format on a USB stick. I can give two of my friends a copy of this; they can do the same, and so on. With thousands of eventual copies going around, it will be impossible to establish which was the real version I own and which I ideally wanted to use in exchange for royalties. By the way, if I ever had to create a song and recorded it, I doubt very much that I would garner thousands of fans. I am just not David Grohl 😊
This is where Blockchain comes in. It is a shared ledger that is used to record any transaction and track the movement of any asset whether tangible, intangible or digital (such as my mp3). It is immutable, so participants cannot tamper with entries, and it is distributed, so all participants share and validate all the entries.
Blockchain will allow “my fans” 😊 to enter into a contract with me directly. As they stream the song, payment goes directly from their wallet into mine. The information about what was listened to and what I was paid, is verified by all the databases in the network and cannot be changed. There are no middlemen (like a central streaming service, or a record label), so the contract (a digital smart contract) is between those that listen to my song and me directly.
It is at this point important to mention that Blockchain is not Bitcoin, or any other cryptocurrency, although it did start life as the technology that underpins cryptocurrencies. This article, the first in a series of three articles, looks beyond its use in cryptocurrencies, and rather highlights use cases to show CxO’s why it is so important to take note of Blockchain and to start controlled proof of concepts (POC’s) and research and development (R&D) in this technology now. We look at some examples across a wide range of industries and use a Courier based use case to delve deeper into what Blockchain could mean for organisations using the Internet of Things (IoT).
Dope testing and cheating have been quite topical lately with large portions of the Russian contingent banned from the Rio Olympics in 2016, and again from the Winter Games in South Korea in 2018 for systemic manipulation of tests. Blockchain will make the test results immutable and open the results up to all that participate in the data cycle. Even if the athlete changes sports, that data will be available to participating sporting organisation. http://www.vocaleurope.eu/how-technology-can-transform-the-sports-domain-blockchain-2-0-will-boost-anti-doping-fight-sports-investments-and-e-sports/
Some countries are planning health data exchanges with the aim of addressing a lack of transparency and improving trust in patient privacy as well as fostering better collaboration. Blockchain will provide practitioners and providers with better access to health, patient and research information. Adoption of Blockchain will lead to closer collaboration and better treatment and therapies, sooner.
Blockchain in healthcare is real and imminent. This study from IBM shows how pervasive Blockchain is expected to become with 16% of 200 responding health executives aiming to implement a Blockchain solution shortly. https://www.ibm.com/blogs/think/2017/02/Blockchain-healthcare/
Australia’s Commonwealth Bank collaborated with Brighann Cotton and Wells Fargo to undertake the world’s first global trade transaction on Blockchain between independent banks – an unbroken digital thread that ran between a product origin and its final destination, capturing efficiencies by digitising the process and automating actions based on data. https://www.commbank.com.au/guidance/business/why-blockchain-could-revolutionise-the-shipping-industry-201708.html
CommBank is taking this a few steps further with an appointed head of Blockchain and a whopping 25 proof of concepts over the past five years, including the ability to peer-to-peer transfer of funds offshore within minutes rather than days, and the issuing of smart contracts. http://www.innovationaus.com/2017/12/CBA-outlines-a-blockchain-future
Customers and insurers will be able to manage claims better, transparently and securely. Claim records, which are tamper proof once written to the chain, will streamline the claim process and minimise claimant fraud such as multiple claims for the same incident.
With Smart Contracts, payments can be triggered as soon as certain minimum conditions are met. There are also many smart contract rules that could ascertain when a claim is also fraudulent automatically denying the claim. https://www2.deloitte.com/content/dam/Deloitte/ch/Documents/innovation/ch-en-innovation-deloitte-Blockchain-app-in-insurance.pdf
Couriers deliver millions of items each day, very often crossing vast geographical distances and across multiple sovereign boundaries with unique laws and processes.
These businesses, who often make heavy use of IoT devices, will benefit hugely from Blockchain to improve the ability to track every aspect of a package delivery cycle and minimise fraud.
There were 20 billion connected IoT devices in 2017 and projected to grow to 75 billion by 2025. https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/
The current centralised approach for insertion and storage of IoT data (see the image below) simply won’t be able to cope with volume demands and transactional contracts will have to rely on multiple 3rd parties. Also Managing data security can be very complex because data will flow across many administrative boundaries with different policies and intents.
In contrast, the Blockchain decentralised peer-to-peer approach for insertion and storage of IoT data eliminates issues with volume demand, (the data is stored across a potentially unlimited number of databases). There is no single point of failure that can bring the whole IoT network to a halt (computation and storage is shared and there is no one primary). It supports tamper-proofing (all participating databases validate a transaction, which is then shared and becomes immutable), which means increased security from rogue participants such as IoT device spoofers and impersonators (Spoofing can occur when security is breached through a lowly secured device on a shared IoT network. If the lowly/ unsecured device is hackable, then the whole network is compromised as it will believe that the hacker is encrypted as the intruder is on it through the easily hacked device).
In a courier parcel delivery ecosystems, the movement of parcels is tracked every step of the delivery process via IoT devices that reads a barcode, or another form of identification that can be picked up by the sensor. From the original warehouse to a vehicle, a plane, another warehouse, and finally your home.
By using Blockchain, each sensor participates in the chain and records “possession” of the delivery item (and so also the location). Each time it is read by a new sensor, the new location is broadcast to, inserted, then shared and agreed on by the remaining participants on the Blockchain. Every block is subsequently a transaction that is unchangeable once inserted into the blockchain.
Each Blockchain entry (i.e. the barcode, the location of the package and a date-time stamp) is encrypted into the Blockchain. The “possession” steps are tracked no matter who is involved in the package delivery process (from the origin which could be the delivery at an Aus Post outlet, to an Aus Post vehicle to the airport, to QANTAS en route to the US, to a DHL distribution centre in a US airport, and finally to a DHL delivery vehicle en route the destination address). This enhances trust in the system as there is no need to adhere and interface with a single primary system, and package tracking is put on steroids. If you have ever sent anything abroad, you would know that granular tracking effectively ends at the border. This won’t be the case with Blockchain. https://www.draglet.com/Blockchain-applications/smart-contracts/use-cases
It must be noted that Blockchain technology has not been around for very long and is rapidly evolving. Widespread commercialisation beyond cryptocurrencies is still in its infancy. But all indications are that it will be a hugely disruptive technology.
The many examples of important players taking this technology seriously move Blockchain beyond hype:
CxO’s may ask, why to invest in something they cannot yet fully understand, but this was probably a very similar question asked in the 90’s about the internet. The learning curve will no doubt be steep, but that makes investing in targeted R&D and POC’s early all the more important so that they do not get caught off guard once commercialisation starts increasing.
In the next article, Blockchain, lifting the lid on confusing concepts, we will delve a little bit deeper and describe the concepts in more depth.
Credit Union SA tracks school rewards based on student family members’ subscription to eligible banking and insurance products. This solution includes dynamic historical data tracking and automates large portions of the business process that previously required a lot of manual intervention.