Data Mesh: Understanding Its Applications, Opportunities, and Constraints 


Data has experienced a metamorphosis in its perceived value and management within the corporate sphere. Previously underestimated and frequently discarded, data was often relegated to basic reports or neglected due to a lack of understanding and governance. This limited vision, combined with emerging technologies, led to an overwhelming influx of data, and nowhere for it to go. There was little to no governance or understanding of what data they had, or how long they had it.  

In the early 2000s, enterprises primarily used siloed databases, isolated data sets with limited accessibility. The 2010s saw the rise of Data Warehouses, which brought together disparate datasets but often led to bottlenecks. Data Lakes emerged as a solution to store vast quantities of raw data and quickly became swamps without adequate governance. Monolithic IT and data engineering groups would struggle to document, catalog, and secure the growing stockpile of data. Product owners and teams that would want, or need access to data would have to request access and wait. Sometimes those requests would end up in a backlog and forgotten about.  

In this new dawn of data awareness, the Data Mesh emerges as a revolutionary concept, enabling organizations to efficiently manage, process, and gain insights from their data. As organizations realize data’s pivotal role in digital transformation, it becomes imperative to shift from legacy architectures to more adaptive solutions, making Data Mesh an attractive option.  

 

The Basics of a Data Mesh 

The importance of personalized customer experiences should not be understated. More than ever, consumers are faced with endless options. To stand out from competitors, businesses must use data and customer behavior insights to curate tailored and dynamic customer journeys that both delight and command their audience. Analyze purchasing history, demographics, web activity, and other data to understand your customer, as well as their likes and dislikes. Use these insights to design customized customer experiences that increase conversion, retention, and ultimately, satisfaction.  

When discussing data architecture concepts, the terms “legacy” or “traditional” imply centralized data management concepts, characterized by monolithic architectures developed and maintained by a data engineering organization within the company. Business units outside of IT would often feel left in the dark, waiting for the data team to address their specific needs and leading to inefficiencies. 

First coined in 2019, the Data Mesh paradigm is a decentralized, self-service approach to data architecture. There are four central principles that Data Mesh is based on: Domain ownership, treating data as a product, self-service infrastructure, and federated computational governance. 

With Data Mesh, teams (Domains) are empowered to own and manage their data (Product). This requires stewardship at the team level to effectively manage their own resources to ingest, persist and serve data to their end users. Data stewards are responsible for the quality, reliability, security, and accessibility of the data. Data stewards bridge the gap between decentralized teams and enterprise-level governance and oversight. 

While teams enjoy autonomy, chaos would ensue without a federated governance approach. This ensures standards, policies and best practices are followed across all product owners and data stewards.  

Implementing a Data Mesh requires significant investment in both infrastructure and enhancing teams with the resources and expertise required to manage their own resources. It requires a fundamental change in companies’ mindset of how they treat data.  

While a Lakehouse would aim to combine the best of Data Lakes and Data Warehouses, Data Mesh ventures further by decentralizing ownership and control of data. While Data Fabric focuses on seamless data access and integration across disparate sources, Data Mesh emphasizes domain-based ownership. On the other hand, event-driven architectures prioritize real-time data flow and reactions, which can be complementary to Data Mesh. 

data mesh decentralized architecture

When and Where to Implement Data Mesh 

  1. Large Organizations with Data Rich Domains: With large organizations, departments often deal with a deluge of data.  From Human Resources to Sales, each team has their own requirements for how their data is used, stored, and accessed. As teams consume more data, time to market and development efficiency suffer in centralized architectures. External resources and time constraints are often the biggest issue. By implementing Data Mesh, teams can work independently and take control of their data, increasing efficiency and quality. As a result, teams can optimize and enrich their product offering and cut costs by streamlining ELT/ETL processes and workflows. 

With direct control over their data, teams can tune and tailor their data solutions to better meet customer needs.  

  1. Complex Ecosystem: Organizations, especially those operating in dynamic environments with intricate interdependencies, often face challenges in centralized data structures. In such architectures, there’s limited control over resource allocation, utilization, and management, which can hinder teams from maximizing the potential of their data. Centralized approaches can curtail innovation due to rigid schemas, inflexible data pipelines, and lack of domain-specific customization. Data Mesh offers organizations the flexibility to adapt to evolving data needs and utilize domain-specific expertise to curate, process, and consume data tailored to their unique requirements. 
  1. Rapidly growing data environments: Today’s digital age sees organizations collecting data at an unprecedented scale. The sheer volume of data can be overwhelming with the influx of IoT devices, vendor integrations, user interactions, and digital transactions. Centralized teams often grapple with scaling issues, processing delays, and the challenge of timely data delivery. Data Mesh addresses this by distributing the data responsibility across different domains or teams. Multiple decentralized units handle the influx as data inflow increases, ensuring timely processing and reducing system downtime. The result is a more resilient data infrastructure ready to meet both current demands and future needs. 

When Not to Implement Data Mesh 

  1. Small to Medium-sized Enterprises (SMEs): While Data Mesh presents numerous advantages, it may not be suitable for all organizations or projects. Smaller organizations typically handle lower data volumes and may not possess the resources needed to manage their data independently. In these cases, a centralized data architecture would be more suitable to minimize complications in design and maintenance with fewer resources to manage them. 
  1. Mature and Stable Centralized Architectures: Organizations usually only turn to new solutions when they are experiencing problems. If a well-established centralized architecture is performing and fitting the needs of the company, there isn’t a need necessarily for Data Mesh adoption. Introducing a fundamental change in how data is managed is an expensive and disruptive undertaking. Building new infrastructure and expanding team capabilities changing organizational culture takes time.  
  1. Short-term Projects: Implementing a Data Mesh requires significant time and resource investment. The benefits of a Data Mesh won’t be seen when building or designing a limited lifespan project or proof of concept. If a project’s duration doesn’t justify the investment of a Data Mesh or the scope doesn’t require domain-specific data solutions, then the benefits of a Data Mesh aren’t utilized. Traditional data architectures are usually more appropriate for these applications and don’t need the oversight/governance that a Data Mesh requires.

  

Opportunities Offered by Data Mesh 

  1. Scalability: Data Mesh enables organizations to scale their data processing capabilities more effectively by enabling teams to control how and when their data is processed, optimizing resource use and costs, and ensuring they remain agile amidst expanding data sources and consumer bases.  
  1. Enhanced Data Ownership: Treating data as a product rather than a byproduct or a secondary asset is revolutionary. By doing so, Data Mesh promotes a culture with a clear sense of ownership and accountability. Domains or teams that “own” their data are more inclined to ensure its quality, accuracy, and relevance. This fosters an environment where data isn’t just accumulated but is curated, refined, and optimized for its intended purpose. Over time, this leads to more prosperous, more valuable data sets that genuinely serve the organization’s needs. 
  1. Speed and Innovation: Decentralization is synonymous with autonomy. When teams have the tools and the mandate to manage their data, they are not bogged down by cross-team dependencies or bureaucratic delays. They can innovate, experiment, and iterate at a faster pace, resulting in expanded data collection and richer data sets. This agility accelerates data product development, enabling organizations to adapt to changing needs quickly, capitalize on new opportunities, and stay ahead of the curve in the competitive market.  
  1. Improved Alignment with Modern Architectures: Decentralization isn’t just a trend in data management; it’s a broader shift seen in modern organizational architectures, especially with the rise of microservices. Data Mesh naturally aligns with these contemporary structures, creating a cohesive environment where data and services coexist harmoniously. This alignment reduces friction, simplifies integrations, and ensures that the entire organizational machinery, services, and data operate in a unified, streamlined manner. 
  1. Enhanced Collaboration: As domains take ownership of their data, there’s an inclination to collaborate with other domains. This cross-functional collaboration fosters knowledge sharing, best practices, and a unified approach to data challenges, driving more holistic insights.

Constraints and Challenges 

  1. Cultural Shift: Teams may not want to own their own data or have the experience to take on the responsibility. Training initiatives, workshops, and even hiring external experts might be necessary to bridge these skill gaps. 
  1. Increased Complexity: Developing an environment that supports a Data Mesh architecture is not without its challenges. As the Data Mesh model expands, managing the growing number of interconnected resources and solving integration issues to ensure smooth communication between various domains can be a considerable obstacle. Planning appropriately to support teams with access, training and management of a Data Mesh is critical to its evolution and success. This includes well defined requirements for APIs, data exchange, and interface protocols. 
  1. Cost Implications: Transitioning to a Data Mesh could entail substantial upfront costs, including hiring additional resources, training personnel, investing in new infrastructure, and possibly overhauling existing systems. 
  1. Governance: Data Governance has become a hot topic as data architectures grow and mature. Ensuring a consistent view of data across all domains can be challenging, especially when multiple teams update or alter their datasets independently. Tools to manage integrity, security and compliance are a requirement in a Data Mesh architecture. The need for teams to have autonomy in a decentralized environment is balanced with a flexible but controlled governance model that is the foundation for federated governance. This can be a challenge when initially designing the model based on team requirements, but it’s an important step to take as early as possible when building a data platform.  

Skillset: Evolving with the Data Mesh Paradigm

With an evolved mindset, the Data Mesh paradigm demands expertise that may not have previously been cultivated within traditional data teams. This transition from central data lakes to domain-oriented data products introduces complexities requiring a deep understanding of the data and the specific use cases it serves, both internally and externally. Skills such as collaboration, domain-specific knowledge translation, and data stewardship become vital. As data responsibility becomes decentralized, each team member’s role becomes more critical in ensuring data integrity, relevance, and security. As data solutions evolve, teams must adopt a mindset of perpetual learning, keeping pace with the latest methodologies, tools, and best practices related to managing their data effectively. 

Embracing the Data Mesh

In the evolving landscape of data management, the Data Mesh presents a promising alternative to traditional architectures. It’s a journey of empowerment, efficiency, and decentralization. The burgeoning community support for Data Mesh, evident from the increasing number of case studies, forums, and tools developed around it, underscores its pivotal role in the future of data management. However, its success hinges on an organization’s readiness to embrace the cultural and operational shifts it demands. As with all significant transformations, due diligence, meticulous planning, and an understanding of the underlying principles are crucial for its fruitful adoption. Embracing the Data Mesh is more than just a technological shift; it’s a paradigm transformation. Organizations willing to make this leap will find themselves not just keeping up with the rapid pace of data evolution but leading the charge in innovative, data-driven solutions.  

Digital Transformation Trends that Future-Proof Your Business


The core of future-proofing your business lies in the incorporation of cutting-edge technological trends and strategic digitization of your business operations. Combining new, transformative solutions with tried-and-true business methods is not only a practical approach but an essential one when competing in this digital age. Using the latest digital transformation trends as your guide, start envisioning the journey of future-proofing your business in order to unlock the opportunities of tomorrow. 

#1 Personalization  

The importance of personalized customer experiences should not be understated. More than ever, consumers are faced with endless options. To stand out from competitors, businesses must use data and customer behavior insights to curate tailored and dynamic customer journeys that both delight and command their audience. Analyze purchasing history, demographics, web activity, and other data to understand your customer, as well as their likes and dislikes. Use these insights to design customized customer experiences that increase conversion, retention, and ultimately, satisfaction.  

#2 Artificial Intelligence  

AI is everywhere. From autonomous vehicles and smart homes to digital assistants and chatbots, artificial intelligence is being used in a wide array of applications to improve, simplify, and speed up the tasks of everyday life. For businesses, AI and machine learning have the power to extract and decipher large amounts of data that can help predict trends and forecasts, deliver interactive personalized customer experiences, and streamline operational processes. Companies that lean on AI-driven decisions are propelled into a world of efficiency, precision, automation, and competitiveness.  

#3 Sustainability 

Enterprises, particularly those in the manufacturing industry, face increasing pressure to act more responsibly and consider environmental, social, and corporate governance (ESG) goals when making business decisions. Digital transformations are one way to support internal sustainable development because they lead to reduced waste, optimized resource use, and improved transparency. With sustainability in mind, businesses can build their data and technology infrastructures to reduce impact. For example, companies can switch to more energy-efficient hardware or decrease electricity consumption by migrating to the cloud.  

#4 Cloud Migration 

More and more companies are migrating their data from on-premises to the cloud. In fact, by 2027, it is estimated that 50% of all enterprises will use cloud services1. What is the reason behind this massive transition? Cost saving is one of the biggest factors. Leveraging cloud storage platforms eliminates the need for expensive data centers and server hardware, thereby reducing major infrastructure expenditures. And while navigating a cloud migration project can seem challenging, many turn to cloud computing partners to lead the data migration and ensure a painless shift.  

Future-Proof Your Business Through Digital Transformation with Kopius

By embracing these digital transformation trends, your company is not only adapting to the current business landscape but also unlocking new opportunities for growth. Future-proofing your business requires a combination of strategic acumen and technical expertise. This is precisely where a digital transformation partner, who possesses an intimate grasp of these trends, can equip your business with the resources and solutions to confidently evolve. Reach out to Kopius today and let’s discuss a transformational journey that will future-proof your business for the digital future.  

A Step-By-Step Guide to Customer Experience Personalization


Winning the interest and loyalty of customers means more than just offering a superior product or service. The secret lies in a powerful strategy called personalization – a dynamic approach that tailors the customer experience to meet individual needs and preferences. As businesses across industries strive to create lasting connections with their customers and meet their evolving expectations, the importance of personalization in the customer experience should not be overstated. Read on to explore the compelling case for customer personalization and a step-by-step guide on how your business can embark on this journey to elevate the customer experience. 

Let’s face it, generic offerings are outdated. Today, customers yearn for something more; they want an experience that resonates with their unique tastes. Personalization is the magic ingredient that taps into this desire. By tailoring products, services, and interactions to individual preferences, businesses create a sense of connection that fosters lasting loyalty. And beyond that, research from McKinsey found that companies who implemented a personalization strategy generated 40% more revenue than their counterparts who placed less emphasis on this approach. All signs point to tailored customer journeys.  

Data lies at the heart of personalization, offering insights into customer behaviors. More than ever, companies have access to a wealth of customer information, such as past purchases and browsing habits, that act as the building blocks to these insights. Leveraging advanced analytics and artificial intelligence, businesses can uncover valuable patterns and trends, guiding them to craft personalized experiences for their customers. 

Building a successful personalization strategy requires thoughtful consideration and calculated execution. If you are just getting started, follow these steps to build an improved and tailored customer experience that will drive remarkable results for your business:

Step 1: Gather as Much Customer Data as Possible.

At the core of every successful personalization strategy lies a deep understanding of your customers. To lay this solid foundation, start by gathering valuable data from multiple touchpoints along their journey, including website interactions, purchase history, and customer feedback. Take advantage of powerful tools like customer relationship management (CRM) software, website analytics, and social media insights to gain a holistic view of your customers’ preferences, behaviors, and pain points.

Step 2: Divide Your Customers Into Audience Segments.

With an abundance of data at your fingertips, it is time to move on to segmentation. Divide your customers into distinct groups based on shared traits like demographics, purchase behavior, and interests. Audience segmentation empowers you to personalize your messaging or offerings, address individual customer needs with accuracy, and create a sense of relevance.

Step 3: Get Personal With Your Messaging.

Now that you have completed the segmentation process, it’s time to get personal! Start by creating interesting content with tailored product recommendations, and design exclusive offers that cater specifically to the unique preferences of each of your audience segments. By doing so, you will create truly personalized experiences that captivate your audience and leave an impression.

Step 4: Automate Dynamic Content Delivery. 

Offer real-time digital experiences that resonate with your customers’ interests and past interactions. Embracing innovative technologies like artificial intelligence allows you to analyze customer data, predict behavior, and implement an effective personalization strategy that delivers tailored experiences on the fly. AI-powered chatbots take personalized support a step further, offering instant assistance to resolve customer concerns and boost overall customer satisfaction levels.

Step 5: Track Your Personalization Campaigns. 

Monitor the impact of your personalization strategy on customer engagement, satisfaction, and business performance. Evaluate key metrics like conversion rates and customer retention to assess their effectiveness. Utilize any insights gained to identify areas for improvement and modify your approach accordingly. 

The possibilities for designing a personalized digital experience are limitless. AI-powered chatbots provide real-time personalized support, making customers feel valued and cared for. Dynamic content delivery ensures website experiences are based on individual preferences. Personalization will enrich the customer journey, increasing engagement and conversion rates. If you are ready to deliver personalized experiences, Kopius is here to help. Let’s team up to create extraordinary customer experiences for your business! 

Elevating Customer Experience Through Digital Transformation


With customers having countless options at their fingertips, the importance of delivering seamless customer experiences cannot be overstated. Offering a great product or service is no longer enough. In today’s fast-paced online world, businesses must go above and beyond to ensure each touchpoint in the customer journey is exceptional if they want to stand out from the competition.  One key solution that has emerged to help companies stay relevant and meet growing customer expectations is digital transformation. IBM defines digital transformations as a customer-driven, digital-first strategy that uses “AI, automation… and other digital technologies to leverage data and drive intelligent workflows… that drive faster and smarter decision-making.” But why should companies who are looking to improve the customer experience invest in digital transformation? The benefits of shifting to a digital-first business model are plentiful, impacting those both inside and outside of the organization.  Let’s delve deeper into how adopting a digital transformation strategy can supercharge the customer experience and benefit your business.

Offer Seamless Omni-Channel Experiences

Meeting and exceeding customer expectations requires delivering a consistent and continuous experience, regardless of which channel they choose to utilize. By integrating mobile applications, social media, websites, and other online platforms, digital transformations allow customers to interact with businesses through their preferred channels. Providing this level of convenience means customers can start their journey on one channel and easily continue to another without skipping a beat. 

Deliver Personalization and Customization to Increase Customer Engagement

Research by Accenture showed that 91% of customers preferred brands that offered relevant offers and recommendations. Digital transformations help businesses unlock the power of customer data, by collecting and analyzing vast amounts of information to derive meaningful insights in a matter of seconds. By tapping into advanced data analytics and artificial intelligence, companies can gain valuable knowledge about buying behavior, preferences, and trends. This helps pave the way for targeted promotional campaigns, individualized interactions, and tailored product recommendations, cultivating elevated customer satisfaction. 

Decrease Downtime, Increase Efficiency 

Inquiries, requests, or the occasional complaint are inevitable, but how your business handles them can be a make or break for your customer. Swift and efficient customer service and support is a must. Digital transformations empower businesses to optimize processes and minimize response times, resulting in expedited customer interactions. Through automation technology, AI-powered chatbots, and self-service options, companies can deliver immediate support around the clock. Thus, customers are able to engage with brands at their desired time and place. 

Digitally transforming the customer experience is a necessity for businesses wanting to thrive in the digital era and offer seamless, tailored experiences. Ensuring speed, customization, and convenience across multiple channels leads to improved customer satisfaction and loyalty, driving tangible return on investment (ROI) for your brand. Are you ready to elevate your customer experience to new heights? Contact Kopius so we can create remarkable customer experiences that will drive your goals and revenue forward!

Valence Group and MajorKey’s Latin American Division Combine to Create Kopius, a Nearshore Technology Powerhouse


Rebrand to Kopius Launches New Full Service Nearshore Digital Transformation Partner to Commercial and Public Sector Clients

Seattle, March 20, 2023 â€“ Today marks the launch of Kopius, a nearshore digital solutions business co-located in Seattle and Buenos Aires. Kopius has been formed through the combination of Valence, a Seattle-based digital consulting firm, and the Latin American division of MajorKey, a Chicago-based technology services business. Both companies are part of The Acacia Group, specialist investors in digital transformation companies. Acacia is backing the formation of Kopius to service rapidly growing client demand for the exceptional nearshore digital consulting and delivery teams the combined business offers. MajorKey’s U.S. business will remain focused on the Identity and Access Management market. 

The launch of Kopius transforms the combined company’s value to its commercial and public sector clients. It brings together a highly skilled team drawn from the U.S. and Latin America, capable of working at scale and speed to tackle complex challenges across the array of digital technologies central to effective enterprise transformation. Today Kopius supports nearly 100 U.S. commercial and public sector clients with more than 600 consultants, designers, and engineers. Kopius delivers end-to-end capabilities across digital experience and strategy, technology solutions, and engineering and operational services. 

“This is an exciting day for everyone at Kopius. It crowns the integration of two great companies to create a new digital powerhouse. The whole team is united around the mission to solve digital tech challenges creatively,” said Jim Darrin, Kopius CEO. “Our true value to clients lies in our ability to achieve strategic clarity, build practical solutions for today, and continuously plan for what’s next. That way, we help clients get more value from their technology investments and navigate the future with confidence.” 

“Central to our strategy for Kopius is sustaining a challenging and rewarding home for the best technical talent in the business across the U.S. and Latin America,” said Matias Mazzuchelli, Kopius Chief Operating Officer. “Our work helping some of the world’s biggest brands retain their edge creates an exciting and diverse range of opportunities for consultants, designers, engineers, and developers to work at the cutting edge of technology and innovation. We’re excited to welcome new people to the Kopius family as we grow.”

“The launch of Kopius exemplifies our approach to building stronger businesses that achieve a greater impact for their clients and create new opportunities for their people,” said Tim Matthews, partner with Acacia. “Client demand is growing for the kind of agile, scalable, and high-value digital services that Kopius offers. With such an outstanding team, we know that they will make a major impact in their market.”

The leadership of Kopius combines industry-leading experience in technology strategy, solution design, engineering, and technical recruiting and team-building. Together, they will be relentlessly focused on designing quality solutions delivered by teams drawn from the best onshore and nearshore talent, technically skilled for the problems they solve, and culturally compatible with the clients they serve.

About Kopius

Kopius is a nearshore digital solutions company. We are resourceful and practical leaders of digital transformation. Kopius operates across all stages of the digital transformation journey with integrated consulting, design, and engineering services delivered by nearshore consulting and delivery teams. Applying creativity, curiosity, and resourcefulness to everything we do, we guide clients on their technology journey, helping them adapt to change and exploit new digital advances, driving continuous value from their technology investments. For more information, visit www.kopiustech.com.

About The Acacia Group

The Acacia Group is a specialist investment firm building stronger businesses by harnessing the power of digital transformation. We work closely with management teams as engaged and supportive partners, fostering resilient cultures of collaboration and innovation to make companies more valuable to their clients, employees and co-investors. By empowering skilful leaders, nurturing exceptional talent, investing in innovation and building distinctive brands, we create the qualities business need to achieve lasting success. For more information, please visit The Acacia Group or follow us on LinkedIn.


3 Keys to Unlock Healthcare’s Digital Front Door


The digital front door has become the common name in the healthcare industry for a mobile website or application that unifies the patient experience and connects patients to care across the continuum.  

In short, a digital front door connects and scales the virtual care journey to give patients what they need, when they need it. 

The trend toward self-service in healthcare was already underway when COVID hit, and the pandemic sharply accelerated the demand for digital access to healthcare information. Appointment scheduling is one important aspect of a digital front door experience, and studies find that 40% of appointments are booked after business hours, and 67% of patients prefer online booking. Further, $150 billion annually is estimated as the annual loss from missed medical appointments. (source

Some of our company’s earliest and most enduring clients have been healthcare organizations, and we’ve noticed three keys to success when developing and deploying a digital front door.  

Key to success: Get the right stakeholders involved 

“This is more than a digital shift – the shift to a digital front door requires a culture shift within the organization,” says Yuri Brigance, Valence’s director of software engineering. 

Experience has taught us that having the right people in the room can make all the difference in the success or failure of a major initiative. Especially considering the role that change management plays here – People don’t resist change, they resist being changed. So you need to engage stakeholders from all impacted groups, from frontline workers to back-office operations. This will improve requirements documentation, roadmap planning, and buy-in as the work rolls out. 

 Key to success: Users Drive the Design Strategy 

“While a digital front door is a technology solution, it’s ultimately about humanizing the patient experience,” says Sam To, designer at Valence. 

In the case of a digital front door, the users may be patients, families of patients, or healthcare providers. In nearly all scenarios, people value products that are easy to use, simple to set up, and have a logical progression. This is especially true in a healthcare situation, which may be hypercharged by personal and situational stressors.  

Equitable design should be at the forefront of design decisions because the healthcare organization needs to design for a wide array of users and needs. You can read more about our approach to equitable design here. 

The design phase of the digital front door project should include user interviews, feedback sessions, prototyping, and more. Giving the UX design team access to users early in the process can help to identify the best-case rollout strategy, reveal opportunities to differentiate from competitors, and deliver precisely the right content to users when they need it – all leading to better patient satisfaction scores. 

Key to success: Develop a feature roadmap and strategy for rolling out updates 

“When embarking on a digital effort in healthcare, it’s important to start by understanding which changes you need to see in the organization. Are you pursuing improved patient satisfaction scores? Physician satisfaction? ED/Urgent Care wait times? Quality and safety scores? Each area targeted for improvement may influence priorities differently,” says Malia Jacobson, healthcare content strategist at Valence. 

Many healthcare providers are leaning into digital solutions to address patient satisfaction, reduce service demand, and reduce administrative overhead. In addition to standard features of a digital front door experience, providers should consider designing for experiences such as:  

  • Bill pay 
  • Self-scheduling and care coordination 
  • Provider communication 
  • Information libraries 
  • Find a provider 
  • Imaging library 
  • Patient outreach 
  • Capacity management 
  • Census management 
  • Forecasting 
  • Infectious disease tracking 
  • Discharge planning 
  • Privacy and security to safeguard patient data 
  • Strategies to increase adoption, such as gamification and push notifications 
  • Support for population health initiatives 
  • Analytics and insights to derive more value from data 
  • AI features, such as chatbots, to reduce clinical burden and improve patient flow 
  • Support for healthcare information exchange in compliance with FHIR standards and best practices. 

It’s important to understand how these features interplay as part of a big picture roadmap with a rollout timeline and strategy. You don’t have to release everything at one time to be successful, and adding features as the platform develops and collects user feedback will future-proof the effort. 

In closing, healthcare has always been heavily impacted by technology, but the patient experience lagged behind other healthcare innovations. That is changing. 

Additional Resources: 


Cloud Migration and Cloud Services


By Luca Junghans

A look inside these cloud capabilities

By joining forces, Valence and MajorKey offer an even greater set of cloud services for businesses that want to power their digital transformation with cloud technologies. 

MajorKey works with clients to migrate business applications to the cloud, and Valence builds services on the cloud. This is one reason these businesses are such a powerful combined force. 

The cloud refers to software and services that run on a (usually) regionally located server owned by the cloud service provider, instead of on an on-premise server owned by a customer. Cloud servers are in data centers all over the world. By using cloud computing, companies don’t have to manage physical servers or run software applications on their own machines. 

It’s big business. In fact, one of our partners, AWS contributed 14.5% of revenue to Amazon’s overall business in 2021, which would have operated at a $1.8 billion loss in Q4 without it – and AWS revenue was up nearly 39% compared to 2020. 

There are many ways to use and understand the business impact of cloud technology. We are breaking down the distinction between cloud services and cloud migration for you here!

Cloud Migration and Cloud Services 

Simply put, cloud migration is what happens when a company moves some or all of its software onto cloud servers.

In other words, cloud migration is moving your software to a managed server operated by the cloud provider; and cloud services are technology solutions built on top of those managed servers. There’s a whole range of capabilities bridging the two. 

Let’s take a closer look.  

Cloud services range in how much they abstract away from the customer.  A good example is Amazon Cognito, which is a user management cloud service. Amazon Cognito has implementations of basic user functions such as login, logout, sessions, and security, so a customer doesn’t have to worry about a deeper technical implementation of these features and can focus on managing users.  

Cloud services are so flexible that there are seemingly infinite ways to deploy them for a business. Cloud services are the infrastructure, platforms, and software hosted by cloud providers, and there are three common solutions:   

  1. Infrastructure as a service: The renting out of virtual machines and space to customers, while providing a way to remotely manage the resource. When a company migrates to the cloud, they are using this service. 
  2. Platforms: Providers like AWS and Azure build specialized software on top of their own cloud hardware and offer the software to customers as a service. These are specialty services and can provide patterns for things such as Data Analysis, Compute, IoT, APIs, Security, Identity, and Containerization. We wrote about Digital Twins in a previous post, which referenced Digital Twin platforms offered by AWS and Azure.  
  3. Software as a service (SaaS): Software can be built on top of the platforms offered by the cloud providers. Software developers can also partner with other third parties to provide fully built instances of software that typically come with subscription rates, customer support, and personal configurations of the software. Examples of this include Atlassian Jira and Confluence, Dropbox, Salesforce, and G suite. 

These services can be transformative for businesses in general, but it’s not always easy to know the best way for your business to use them. The added benefits to this migration range per case, and here are four examples: 

  • Scalability: Cloud services often offer on demand scaling options that can satisfy unexpected or planned growth. Depending on your product, this can be a lot easier than upgrading on-premise hardware, but not always cheaper. 
  • Cost: Although we expect the costs to be passed to the consumer in some way, the logistics of maintenance and upgrades to the cloud systems is handled by the provider. In many cases this can translate to a huge amount of money saved for the customers. 
  • Performance: Performance-enhancing services like CDNs and regional hosting, when understood and configured properly, can have tangible and positive performance impacts. 
  • Local Management: Being on the cloud means access to the digital portals to manage the services (most times). This creates a lower bar of entry for employees to manage and observe the resources. 

Many businesses start their digital transformation journey by migrating infrastructure or applications from on-premises servers to the cloud. Notably, cloud migration can also refer to a situation where a business needs to bring the cloud resources they manage into an on-premises environment. It can also describe a situation where a business moves its data resources from one cloud provider to another.  

Cloud migration to use cloud services is a process that presents many upsides, and is worth investigating!  The process will add additional complexities – specifically, security and governance will generally be instituted upfront as a base for the rest of the migration. We design and engineer performant, scalable, and maintainable applications that save businesses money, fill in knowledge gaps, and provide users with a positive experience.  

Here are two examples of cloud services that we’ve built for clients:  

  • Building cloud applications with AWS lambda: We have bridged the gap between multiple third-party APIs and created new databases that consolidate data and deliver it to a web application. Cloud services remove the need for our clients to interact with these multiple services, which saves them time and money. At the same time, we used AWS Cognito to help our customer manage roles and users in a secure and trusted way. This removed the need for our engineers to write our own user management software, a cumbersome task. 
  • Data pipelines:  We identify problems in our customers’ current database providers and migrate data to a more performant and better structured database in cloud-to-cloud migrations.  

We will continue to build and migrate while we investigate the future of the cloud. What are the new services and platforms? Who can benefit the most from them? How can we do it right? We will be prepared for the cloud migration and services needed from the real world to the metaverse, and beyond.  

Additional Resources:  


The Right Data Retention Policy for Your Organization


by Steven Fiore

Every business needs a strategy to manage its data, and that strategy should include a plan for data retention. Before setting a data retention policy, it’s important to understand the purpose of the policy and how it can contribute to organizational goals. 

There are four values that drive most businesses to do anything:  

  • To make money and increase revenue
  • To save money by decreasing costs
  • Because they must comply with regulations
  • Because they want to use the business as a platform for social good

While each of these values will be represented in any organization, some investigation will usually reveal that one or two of these values outshine the rest. Which values are most important will vary from one organization to another. 

Organizations need to start by clearly stating the goals of their data policy, and then build a policy that supports those goals. We help companies unearth business drivers so data policies can contribute to the company values and goals rather than compete with them. 

In this post, we explore best practices in establishing and maintaining a data retention policy through the lens of these business drivers.  

What are the goals of your data retention policy?

Value: Make Money

Companies that rely on advertising revenue like Google and Facebook want to keep as much data as necessary to maximize revenue opportunities.  

Companies that mine their data can spot trends in their data that inform product enhancements, improve customer experience (driving brand loyalty), and reveal revenue opportunities that would have otherwise been hidden. 

In both cases, the data retention policy should focus on what data can contribute to revenue, and how much of it is needed. Balancing aggregate data versus more granular data is the key so you retain enough data to achieve your objectives without retaining unneeded data that adds cost, complexity, and security or privacy risks.   

Value: Save Money

Many businesses focus on the bottom line and prioritize efficiency to avoid wasting time, money, and energy. 

Businesses that want to save money can use data retention to make the organization more efficient. While data storage is inexpensive, it isn’t free – and access can be more expensive than storage. So, for an organization that wants its data policies to help save money, the policy might focus on retaining only the data that is necessary to avoid extra storage and management overhead. 

Further, retaining more data than you need to can be a legal liability. Having a data retention and disposal policy can reduce legal expenses in the event of a legal discovery process.  

There’s also an efficiency cost to data – the more data you have, the slower the process will be to search and use that data. So, data retention policies can and should be part of a data governance strategy aimed at making the data that is retained as efficient to manage and use as possible. 

Value: Comply with Regulations

Many industries have their own regulations while some regulations cross industries. Businesses that must have a data retention policy may need it to comply with laws that govern data retention such as the Sarbanes Oxley Act, the Health Insurance Portability and Accountability Act (HIPAA), or IRS 1075. Even US-based companies may be subject to international legislation such as the European General Data Protection Regulation (GDPR), and companies that have customers in California need to understand how the California Consumer Privacy Act (CCPA) can impact data retention. Government agencies in the US are also bound by the Freedom of Information Act and some states have “Sunshine” laws that go even further.  

Businesses that are motivated to comply with regulations will need their data retention policy to reflect federal, state, and local requirements, and will need to document compliance with those requirements. 

Value: Business as a Platform for Social Good

 Whether an organization was established as an activist brand or has been drawn to social responsibility as investor demand has risen social responsibility, many companies are finding ways to use data to understand their social and environmental impact.  This impact is often also reported on through Environmental Social Governance (ESG) reporting, Carbon Disclosure Projects, and reporting structures like GRESB (Global Real Estate Sustainability Benchmark). 

In these cases, organizations that use their business as a platform for social good, may identify key metrics such as energy consumption or hiring data that can be used to inform reports on social responsibility.  

In closing

By understanding your organization’s values and priorities, you can ensure that its policies support those values. Every company has data to collect, manage, and dispose of, so it’s critical to have a roadmap for how to address data requirements today and into the future. This framework is a starting point to that effort because there’s nothing worse than going through the effort to implement a complex policy, only to discover that it moves the business further from its goals.  

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