UiPath & Azure: Data Driven Efficiency

By | Automation Initiation, Data Platform, Enterprise PowerBI | No Comments

At Talos our goal is simple: to deliver data-driven efficiency. In our experience, the best way to achieve this technically has been through the combination of UiPath & Azure – two very powerful technology stacks that when paired properly will deliver immense value. This blog post examines the relationship between UiPath & Azure, a typical design & use-case, and the data driven benefits of leveraging both together.

     

 

UiPath & Azure

UiPath is the world’s leading RPA company delivering a suite of automation technologies targeted at the enterprise level. Azure is Microsoft’s cloud platform, offering a vast array of services to customers to meet their complex needs. Given the technical strengths of each, it is possible to craft a solution that utilizes both to achieve optimum benefits, and in our case, deliver our goal of data-driven efficiency.

In numerous projects we have worked on, there has been a typical requirement to deliver reporting based on the combination of data from a variety of sources. This simple use-case can actually be quite complex, especially when dealing with legacy data source systems, large volumes of data and a significant reporting consumer-base. However, these requirements can be met with a very straight-forward UiPath & Azure solution design:

UiPath & Azure

This design is composed of the following individual elements:

  1. Azure VM’s
    1a. UiPath Studio
    1b. UiPath Unattended Bot
  2. Azure Blob Storage
  3. Azure Data Factory
  4. Azure DevOps
  5. Azure SQL Database
  6. Power BI

Each of these elements have a specific role in the solution, and fit in easily with each other, making this solution extremely robust, easy to initiate and  scalable.

  1. Azure VM’s

Azure Virtual Machines (VM) are the image service instances that provide computing resources that behave exactly like physical infrastructure, except virtually. The benefits of Azure VM are the on-demand nature of the product and the lower costs associated with management. In our solution, 2 of these VM’s are commissioned to provide separate environments for the UiPath tool:

1a. UiPath Studio is installed on the first VM (this is used as the dev/test environment). UiPath Studio is the development tool used to create and test automations. In our case, we use UiPath Studio to develop the automation steps required to retrieve data from the different legacy systems.

1b. UiPath Unattended Bot is installed on the second VM (this is used as the production environment). Once the automations are developed and tested, they are deployed to be executed by the Unattended Bot on this VM. By having a dedicated VM, this bot acts like a 24/7 worker and is available on the VM to perform any tasks it is instructed to do.

  1. Azure Blob Storage

Azure Blob storage is the scalable and secure object storage service used to store data in a variety of formats. Blob storage is very robust and can scale very easily to suit storage needs. In our case, we leverage Blob storage as a staging area for the bot to store the data it has retrieved, and also serves as a source for the Azure Data Factory pipeline later on. UiPath can communicate with Azure Blob storage natively, making this integration easy and reliable.

  1. Azure Data Factory

Azure Data Factory (ADF) is the data integration service built for complex ETL projects. The benefits of ADF are the ease-of-development as well as the powerful capabilities that allow it to handle complicated data transformations in large volumes. In our case, we use ADF to create a pipeline to move data from Blob Storage into the Azure SQL database, whilst performing sophisticated transformations. Although UiPath possesses some ETL functionality, they lack the advanced capabilities of ADF regarding transformation and speed. For this reason, ADF is a must have in our solution.

  1. Azure DevOps

Azure DevOps (ADO) is the collaboration tool for software development offering work tracking, source control and continuous integration/delivery. ADO allows projects to be managed effectively and collaboratively. In our case, ADO acts as the project management tool and code repository for the ADF pipelines. Although UiPath has a native integration with ADO, it also possesses the source control and deployment capabilities out-of-the-box, and therefore can be managed within the tool itself.

  1. Azure SQL Database

Azure SQL Database (DB) is the cloud-based database service built on the SQL Server engine. It has a wide range of deployment options, making it very easy and effective to manage. In our case, this is where the transformed data is stored and made available for analysis. The scalability, availability and deployment ease of Azure SQL DB make this very attractive for enterprise-level analytics and reporting.

  1. Power BI

Finally, whilst not an Azure service itself, Power BI is used as the reporting tool to develop custom reporting on the data in the Azure SQL DB. Power BI is an excellent reporting platform for enterprise-level reporting due to its scalability and self-service capabilities. With this tool in place, the data is modelled and reported to the business.

Although every project is different, the above represents a good design for a typical solution and is used by us as a list of ‘minimums’ that we need. For our work, this design is very common, but is also great as a default because it can be restructured very easily to suit any additional needs (for example adding Azure Machine Learning can be integrated into the above design as part of a CASSIE deployment). With the above solution, a business can very quickly leverage the benefits of UiPath & Azure working in unison and delivering data-driven efficiencies: businesses are able to get the insights and reporting they need without having to expend any staff time to deliver it.

If you want to know more about UiPath & Azure together, please contact us.

Invoice Processing: The Case For Automation

By | Automation Initiation | No Comments

In the context of business administrative activities, invoice processing is the single most important process to get right. These activities ensure that business operations run smoothly without delay or difficulty. As we have seen before, a slow and unreliable process in the accounts payable department will inevitably contribute to inefficiencies across the wider business, costing both time and money. It’s no coincidence then that there has been an explosion in interest in automating invoice processing. On paper, the advantages of automation such as speed, accuracy and reliability, should work well for invoice processes. Through our work with various businesses, we have been testing this hypothesis – and the results are in. Automation is an absolute necessity. This blog post examines invoice processing in detail, the benefits of invoice automation and how to quickly automate your invoice processes.

Invoice Processing

Invoice Processing

Invoice processing refers to the tasks and activities that businesses perform to ensure that invoices are received, recorded and acted upon in a reliable and timely manner. This process is perpetual – new invoices are received virtually every day and must be actioned immediately to ensure that obligations are met. Typical steps involved include:

  • Receiving invoices in a central location (eg mailbox folder)
  • Validating that the invoice is correct (eg 3 way matching)
  • Recording the data into a system (eg entering the data into an ERP)
  • Confirming receipt of the invoice (eg generating reporting on new invoices)

The details of each task are likely to be different in every business, for example the logic used to validate that an invoice is correct may rely on different factors such as amount thresholds etc. However, the steps remain the same for every business – an invoice is received, recorded and reported.

When comparing invoice processing principles to automation benefits, it becomes clear that automation is a good fit:

  • Processing is speed sensitive –> bots are quicker at performing tasks than humans
  • Processing relies on accuracy –> bots do not make mistakes or ‘human errors’
  • Processing must be timely –> a bot is a reliable, ‘24/7’ worker

Invoice Automation Benefits

After automating your invoice processing, the obvious benefits you can expect include:

  • Happier suppliers, as their invoices are processed quicker and are not missed
  • Happier staff, as they are no longer performing this low-value task
  • Better cashflow management, as you are recording invoices quickly and more accurately, allowing you to plan finances ahead of time
  • Reduced risk of unexpected expenses due to mishandled invoices

The above benefits are the most common. However, depending on your business, there are some other features to automation that may be beneficial:

  • Invoice processing in your business may be more complex and require stages of approval. Automation technology, particularly UiPath, make it very easy to design a hybrid-process, whereby a bot performs certain tasks and hands it off to a human for approval. This combination of human and bot has the effect of augmenting each other and can deliver greater efficiency.
  • Before undertaking an automation project, a careful review of the existing processes takes place. During this phase, it is not uncommon for businesses to identify issues or inefficiencies in their processes, especially if the process is either very new or very old. After identifying these issues, businesses can take action to improve them, and drive further efficiencies.

How To Automate Your Invoice Processing

The key with automating your invoice processing is to define your process in detail. This includes all the systems involved, the steps performed, the logic used and the possible exceptions that may arise. Once you have defined these, the actual work in automating the process becomes much easier. In fact, having gained significant experience with invoice processing, Talos has designed and released ROBBIE – our Robotic Invoicing Expert. So much of our work has been in delivering a common invoice processing solution, that we have developed a bot that can learn any invoice process quickly and execute it reliably. ROBBIE has been trained to specifically work on invoice processing and is already in use across Australia. If you want to get started, deploying ROBBIE in your business is quick and easy – better yet, he can start working immediately and returning value in your business.

If you want to know how to automate invoice processing, please contact us.

Meet our New Automated Processing Bots!

By | Automation Initiation | No Comments

Having been secretly working hard over the past 12 months, Talos is excited to finally announce our new bots for 2022! We are pleased to present to you CASSIE, ROBBIE & CORRIE, our newest additions in the automated processing space. In this post we will introduce each bot, highlighting their expertise, abilities and why you need to hire them as part of your team.

automated processing

CASSIE

One of the most popular areas for automation is in the customer service space – in fact, most of our work in 2021 was focused on this key area. Therefore, to help businesses increase their efficiency in customer-related processes, Talos is proud to present CASSIE – our Customer Assisted Intelligent Expert.

Like all our bots, CASSIE is built on the UiPath platform, and has been rigorously trained using RPA best practices and real-world business process lessons. Her specialty is in delivering efficiency in customer processes such as:

  • Customer on-boarding
  • Customer cleansing
  • Mail triage & customer communications
  • Customer reporting

CASSIE can be trained to follow any customer-related process, as she can learn processes quickly and follow them reliably. At a high-level, her abilities include:

  • Extracting and validating customer data from any data source
  • Leveraging Machine Learning to classify mail and customers
  • Reading and writing data to CRM and ERP systems

With CASSIE as part of your team, you can expect:

  • Increased speed in customer processing
  • Increase in staff time to focus on more valuable tasks
  • Increase in data quality and reduction in process errors

Some businesses that are already using CASSIE include:

Deploying CASSIE is no different to hiring staff, except CASSIE can learn much quicker, works 24/7 and will not make mistakes. You just need to teach her the process once and she will begin work immediately. Better yet, you can teach her as many processes as you want to – she loves to work and help out!

Automated Customer Processing

ROBBIE

Invoice processing is a pillar of every business and is one of the key areas where automated processing can deliver demonstrable value. For that reason, Talos is excited to introduce ROBBIE – our Robotic Invoicing Expert. ROBBIE is dedicated to delivering efficiency in invoice-related processes such as:

  • Accounts payable processing
  • Accounts receivable processing
  • Statements & Reconciliations
  • Ad-hoc & customer financial reporting

ROBBIE can be trained to follow detailed invoice processing logic including 3-way matching, data validation and document verification. At a high-level, his abilities include:

  • Extracting invoice data from any document or file
  • Matching and validating invoice data based on defined logic
  • Reading and writing data to ERP systems

With ROBBIE as part of your team, you can expect:

  • Increased speed in invoice processing
  • Increase in staff time to focus on more valuable tasks
  • Increase in data quality and reduction in process errors

Some businesses that are already using ROBBIE include:

ROBBIE is not constrained by system and can be implemented on any system or application. Just like a regular staff member, all ROBBIE requires is access and he can do the rest!

automated invoice processing

CORRIE

Compliance processing is a specific and crucial area for businesses. If your process is inefficient or prone to error, your business is at risk of non-compliance which can be very costly. For that reason, Talos is pleased to introduce CORRIE – our Compliance, Regulatory & Reporting Information Expert. CORRIE is skilled in delivering efficiency in compliance-related processes such as:

  • Form data extraction & validation
  • Data cleansing & migration
  • Ad-hoc & custom alerting
  • Document filing & metadata management

CORRIE is our best learning bot – she has been skilled to learn any process very quickly. This is useful in the context of compliance processing where regulatory requirements can change and processes must be updated to ensure compliance. At a high-level, her abilities include:

  • Extracting & verifying data from any document, file or system
  • Easy retraining capabilities for document understanding
  • Reading and writing data to case management systems or document management systems

With CORRIE as part of your team, you can expect:

  • Increase speed in compliance processing
  • Increase in staff time to focus on more valuable tasks
  • Reduction in process errors and the risk of non-compliance

Some businesses that are already using CORRIE include:

CORRIE can easily learn and adapt to processes as they evolve over time, greatly reducing the risk of non-compliance. Much like your best staff, she can be relied on to ensure that your business does not fail in meeting your compliance requirements, whatever they may be.

automated compliance processing

With these new bots available, businesses can easily adopt automated processing and quickly obtain the accompanying benefits. Whether it be automated customer processing, automated invoice processing or automated compliance processing, Talos will continue to train and deliver our bots to any business wanting to achieve their goals of increased efficiency and optimum performance. With CASSIE, ROBBIE & CORRIE on your team, we know you can.

If you would like to meet our bots, please contact us.

PowerBI governance

The need for good PowerBI Governance

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

What needs governing?

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

  • Data
  • Security
  • Platform
  • Users

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

PowerBI Governance – Data

PowerBI governance data

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

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

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

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

PowerBI Governance – Security

Security

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

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

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

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

PowerBI Governance – Platform

Platform

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

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

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

PowerBI Governance – Users

Users

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

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

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

Summary

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

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

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

By | Data & AI, Data Visualisation, Enterprise PowerBI | No Comments

Popular BI Tools in 2022

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

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

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

Graph of search for Popular BI tools

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

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

State of the Self Service BI Market

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

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

What does the future hold for Popular BI tools?

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

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

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

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

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

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