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Robotic Process Automation (RPA) continues to drive enterprise efficiency, automating tasks across diverse sectors. The benefits are strikingly similar regardless of the use case: bolstered security, improved customer experiences, and increased agility.

Done right, RPA transformation unlocks time, money and human capital in the organization, freeing resources to focus on valued-added tasks, and helps IT leaders deliver on business priorities.

As the RPA landscape matures, four tools dominate: SS&C BluePrism, AutomateAnywhere, UI Path, and Microsoft Power Automate. Particularly noteworthy is Microsoft's Power Automate, which, according to Gartner's 2023 Magic Quadrant, not only competes with specialist vendors but is recognized as the most visionary tool.

The Gartner Magic Quadrant reveals that Microsoft has not only risen to match its competitors but has edged forward as the most visionary with Power Automate. This leading position, albeit modest, is a sign of Microsoft's aggressive investment and the swift enhancement of their RPA solutions, outstripping the rate of change seen by others.

What is a Robotic Process Automation (RPA) Tool?

An RPA tool employs 'bots' to replicate rule-based human actions, such as system navigation and data extraction, without needing integrations. This frees skilled workers to focus on innovation. RPA tools enhance productivity through intelligent automation and offer seamless, low-code process automation.

The challenge for many complex organizations is that RPA is typically implemented in silos, resulting in 'bots' that don't communicate with each other without significant human intervention. Layer on the cumulative cost of individual licenses and it’s enough to give pause for thought. Advanced RPA providers integrate their tools with AI, leading to "hyperautomation." However, traditional RPA bots have limitations, such as an inability to interpret complex data or adapt to minor changes in user interfaces, which can disrupt workflows.

Gartner Magic Quadrant Analysis for RPA Tools

Gartner's Magic Quadrant evaluates RPA vendors on their ability to execute and completeness of vision, assessing factors like product or service viability and customer experience.

Discover the Top 4 Leading RPA Tools for 2024

Blue Prism

Blue Prism stands as one of the original RPA tools, carving out a niche in automating complex, enterprise-scale business processes. Predominantly catering to large-scale corporate applications, it exclusively supports unattended automation. Blue Prism's broad suite includes intelligent automation features like data collection, analysis, visual analytics, machine learning, and collaborative automation. Its robust capabilities are a fit for enterprises prioritizing stability and security, especially for back-office operations.

However, critiques have emerged about Blue Prism's responsiveness to customer feedback and the high costs associated with customization and deployment. This resistance to agility may hinder its position as a driver of innovation.

Read G2 Report for BluePrism

UI Path

UI Path differentiates itself with a user-centric design that appeals to a broad user base, from tech-savvy to non-technical staff. It excels in its scalability, catering well to the needs of small and mid-sized businesses with its low initial costs and quick onboarding process.

UI Path's integration capabilities cover both attended and unattended applications, providing flexibility and immediate operational benefits. Despite its advantages, UI Path’s specialized nature means escalating licensing costs as automation scales up, presenting a potential issue for organizations expanding their RPA footprint.

Read G2 Report for UIPath

Automation Anywhere

Automation Anywhere is renowned for its blend of RPA and AI, creating a cognitive automation environment appropriate for a variety of sectors. The platform stands out for its user-friendly interface, enabling beginners and intermediate users to automate complex processes with ease.

Automation Anywhere boasts a supportive community forum, rich in resources like metabots for advanced tasks. Its recognition on platforms like G2 for a robust bot security framework and high compliance standards makes it a trusted option for organizations requiring stringent security measures, particularly in rapid scale-up scenarios.

Read G2 Report for Automation Anywhere

Microsoft Power Automate

Microsoft Power Automate was recognized by Gartner in 2023 as a visionary leader, thanks to its unified approach to automation within Microsoft's integrated suite of technologies. It is particularly adept at managing trigger-based workflows, streamlining simple to moderately complex tasks.

Power Automate's extensive array of connectors allows for rapid integration across various applications within the Microsoft ecosystem, positioning it as an ideal solution for Microsoft-centric enterprises. Notably, it provides substantial licensing cost advantages through enterprise-level bundling, enhancing its value proposition for Microsoft's established clients.

Read G2 Report for Power Automate

Selecting the Right RPA Tool for Your Enterprise:

The choice of RPA tool should be based on factors like integration capabilities and the scale of digital transformation required. There's no one-size-fits-all; the decision hinges on the organization's size, automation complexity, and strategic goals.

For Microsoft Enterprise clients, Power Automate presents a strategic opportunity for integrated and efficient automation, with the potential to free up a huge level of resources locked in the organization. A recent article in Forbes cites a 27.4% improvement in business process efficiency and a 20.7% reduction in errors for organizations adopting Power Automate vs. other RPA solutions.

Sonata Software have a dedicated RPArena, with specialists certified in all four of the leading RPA tools, as well as Bluprint integration technology. We offer a free 2-hour envisioning workshop for enterprises looking to modernize their RPA strategy.

Download Sonata’s NEW RPA Transformation Guide or contact us to explore how we can help you unlock the full potential of RPA modernization for your enterprise.

FAQs:

What are RPA tools and how do they benefit enterprises?

RPA tools automate repetitive tasks, freeing up human resources for higher-value work, thus benefiting enterprises by boosting efficiency and innovation.

How does the Gartner Magic Quadrant influence RPA tool selection?

The Gartner Magic Quadrant helps businesses assess the strengths and weaknesses of RPA vendors, guiding them to make informed decisions based on their specific needs.

What factors should businesses consider when choosing an RPA tool?

Businesses should consider the tool's integration capabilities, scalability, user-friendliness, and alignment with their strategic goals.

We are thrilled to witness general availability announcement of Microsoft Fabric today! This also marks 1 year of amazing journey with Microsoft Fabric. Thanks to product engineering, partner & field teams and internal implementation teams at Microsoft, customers and prospects who engaged with us on early evaluations, pilots and brainstorming; this has really helped Sonata in early learning & adoption, contributing to the product, develop subject matter experts, building our offerings and accelerators.

Excited to be a featured partner for Microsoft Fabric!

Fabric featured partner page

Fabric GA blog by Arun Ulag

Enterprises have already started realizing the immense need of complete and high quality, connected data ecosystem for AI innovations to succeed.

Providing connected data foundation for analytics and AI to our customers is a key focus area for us. Microsoft Fabric provides a perfect technology stack to achieve this.

Real world objects are inherently interrelated. For a true reflection and complete insights, data need to be connected too.

Silos of information can’t provide real world reflections. Because real world entities and events have complex and many-to-many relationship. Insights gathered, inferences derived or AI predictions from silo datasets are at the risk of being inaccurate, incomplete, or impossible!

Here is an example. A retail store chain struggled to estimate their assembled product delivery date to customers at the time of order. Analytics specialists experimented with number of forecasting models to predict the order fulfilment and delivery estimates with limited success.

One of key challenges that prevented the predictability is disconnected information systems. This is a quite common challenge among the enterprises and bridging the silos is often a complex and time-consuming project. Reflecting an integrated picture of the business is key to solving such issues.

Building connected data model for each use case will be time consuming and expensive.

When there are several such needs, implementing integrations for each use case will be slow and expensive. Building connected data foundation on a SaaS platform like Microsoft Fabric is a very relevant solution to solve multiple such challenges quickly and cost-effectively.

Is lack of connected information system the only problem here? In the above example, where the product delivery involved assembling various components from existing inventory or from procurement channels, finding nearest or fastest sources of the parts, shipment routes, predictability of order fulfilment is dependent on variability of many sub-processes. It could appear to be process related challenge but connected data and insights has significant role to play in those sub-processes too. For example:

1. Unpredictable demands
2. Complex supply chain processes.

Demand prediction involves customer and market intelligence. Connecting complex supply chain process involves connecting their data in a business domain context.

Predictability often involves data universe beyond the organizational boundary.

Predicting product demands requires customer intelligence, market intelligence, competition, pricing, discounts and many more. Product or brand’s social sentiment can bring a drastic change in the demand too. Most of these are not internal data sources. Expanding the scope of information and intelligence hence becomes essential to solving some of the key business problems. This is where, what seems to be not related to information challenge, is actually related to it.

Building data mesh is a great way to connect disparate datasets while they physically can’t be all integrated or stored together.

Fabric brings number of key features necessary to build connected data mesh.

Plugging in required dataset into contexts – internal or external through connectors or shortcuts helps quickly build a mesh.

• Shortcuts across workspaces in Fabric allows intra-company datasets connected.
• Cross-platform shortcuts and rich set of data connectors in Fabric allows building an enterprise data model beyond the boundary of technology and systems stack.
• Sonata’s Lightning Data Suite further helps map the datasets into connected domain models and intelligently identify potential relationship across the disparate datasets. More on this in the last section of this blog
• Fabric’s focus is on enabling open and connected data ecosystem. Specialized features such as Synapse Link for Dataverse further simplify and speed up data integration into OneLake.

Connecting business processes involve connecting their data in a business domain context

While connecting datasets coming from supply chain, inventory locations, product part compatibility, pricing and shipment information, relationship between these datasets would seem really complex and hard to define unless they are put into a context of an integrated domain context. Hence, domain modeling is an important aspect of building a connected data foundation.

There are more reasons for organizing data into a connected domain models

1. Domain model simplifies self-service analytics
2. It broadens the audience for usage of data and helps adoption & ROI
3. Improves usage of co-pilot and NLP based data exploration
4. Reduces load on Engineering teams so that they can focus on more innovations and new build rather than getting caught up into fulfilling ad hoc insight needs
5. Greatly improves agility. Users could get their insights in seconds rather than waiting on SME team to deliver it through build cycles
6. Improves role experience by providing relevant perspectives of the enterprise data model
7. Improves security. Fragmented data pieces could fall through the loopholes. Data entities well mapped to the functional domain can be better secured and governed.

Sonata’s domain data model approach is precisely for building that business friendly data structure on a connected data mesh in Fabric platform.

Build connected data foundation using Sonata’s Lightning Data Suite (LDS) for Fabric

LDS connects data silos in many ways.

1. Domain data models bring functional connections among system generated silos.
2. Intelligent mappings connect source data structures to domain models
3. Labeling & tagging, label classifications and keyword synonyms establish similarity
4. Semantic connector discover hidden connections across structured & unstructured data elements

Vision of Lightning Data Suite is to optimize data engineering and sustenance effort in order to leverage more bandwidth towards deriving insights and AI innovations. LDS brings capabilities necessary to build connected data foundation faster.

Domain data dictionary

This transforms system data model to business-friendly semantic data model for analytics and co-pilot, natural language querying and summarization in Fabric Power BI

Automatic Data Pipelines

Using the business dictionary-based metadata, LDS Automatic data pipeline does the job of hundreds of typical data flows or data pipelines that ingest data into data lake and build delta parquet based Lakehouse tables in Fabric.

Semantic connector

Connected data ecosystem is not only about bringing datasets from heterogeneous systems and sources; unless the datasets are meaningfully connected, real data mesh is not formed. LDS Semantic connector intelligently establishes relationships across heterogenous datasets coming together into OneLake.

Sonata LDS also brings various horizontal and vertical use case solutions based on our market research of key gaps and pain-points.

We are helping customers globally with their Fabric based data modernization journey.

We have been doing Fabric briefing sessions to help enterprise stakeholders explore what is in Fabric and how it helps with data modernization. For an enterprise to take a step back and revisit data strategy for the era of transformations with AI, customers leverage joint envisioning sessions. For further deep dive analysis of applicability and validate the possibilities with Fabric based solutions, we provide assessment and Proof of concept services. Data modernization using Sonata’s lightning data suite helps modern enterprise realize business friendly, connected data foundation on Fabric for agile and cost-efficient data modernization.

Behalf of team Sonata, I sincerely thank our early adoption customers for their invaluable questions and inputs, Microsoft Fabric Product Engineering teams for all the guidance and collaboration, Microsoft Field teams for joint GTM efforts and partnership, Microsoft internal solution implementation teams for the opportunity and collaborative early adoption programs. This has helped us in building specializations, co-create and add value to Fabric product ecosystem. Past 12 months of journey with Microsoft Fabric has been amazing and we are looking forward to delivering customer success through innovative data modernization solutions on Microsoft Fabric.

Related links:

• Microsoft partner blog
• Microsoft blog page