Data Ecosystem Modernization
A next-gen, robust, scalable, and fast data ecosystem is the key for customers, suppliers, and employees to collaborate and operate with data at their fingertips.
The past decade has seen an extreme proliferation of data, changing consumer behavior, and intense competition. To remain resilient and pivot as needed during times of great change, leading organizations are continuously evolving data ecosystems throughout their enterprise for optimization, transformation, and innovation. Successful IT leaders, too, responded to disruptions by making smarter decisions, improving efficiencies, enabling business agility, driving innovation, and ultimately beating the competition. And, among all this chaos, data continues to lead in terms of enablement to fully realize future strategies.
If we dig deeper, data storage and processing costs have decreased over the years, whereas the quantity and timeliness of data needs have grown exponentially. As a result, the amount of generated data exploded in terms of the 3V’s Volume, Velocity, and Variety. Such a massive amount of data and the enormous growth rate from infinite sources presents a daunting challenge. Legacy architectures were not designed for the voracious business needs and robust data requirements of today. The demand from businesses to access and analyze their data quickly is a major driver to modernize and continually evolve a data ecosystem. In parallel, the right level of skills and talent needed to make effective use of these newfound data assets has lagged.
What is Data Ecosystem Modernization?
Modernizing data ecosystems can involve all aspects of the business’ value chain but is most often centered around aligning the speed, flow, cleanliness, access, and meaning to your key strategic business drivers. At the core of these efforts is the need to revamp and extend your data infrastructure to effectively reap the benefits of new technology, and in turn, drive speed and agility in your data processes. When done right, a modernized data ecosystem will provide for greater adaptability to changing business requirements while continuing to be a relevant factor in your business decisions, even as data and information needs change.
Due to data explosion, data latency, regulatory demands, and increasing data management costs, traditional enterprise data infrastructure and operational data stores have struggled. Also, with the ever-increasing business process complexities, the legacy systems lacked the speed, flexibility, and scalability to deliver timely and accurate insights. The growth in quantity, diversity, and access speed challenged the status quo for industry players with legacy mindsets. And, with the influence of hyper-connectivity and hyper-personalization, the value realization of data cascaded even to the non-digital world.
Hence, organizations endeavored to modernize their data landscapes and renew their infrastructure to approach zero latency in data and insights. Interestingly, these organizations were from all sizes and shapes, including laggards as well as late adopters. Once modernized, next-gen data platforms are characterized by fast, fault-tolerant infrastructure, a high degree of collaboration, and the ability to process massive volumes of data.
Today, many enterprises are struggling to keep pace in this journey of modernization. This transformation must be evolving and will need to be followed up with strategies for continual modernization. However, existing enterprise data platforms are faced with challenges that prevent them from building an information-driven business culture. And, presenting a business case is one of those challenges.
Making a Case for Modernization
Firstly, data modernization helps build and deliver a data ecosystem that is leaner, agile, and adaptive, empowering enterprises with real-time insights. It allows enterprises to take stock of their current data environment and help them optimize, transform, and digitize it. Ultimately, by reducing the data capture and information processing latency, data ecosystem modernization helps enterprises reduce ‘Time to Insights.’
Further, there will always be a continued ask to achieve reduced latency via a scalable and cost-effective framework. Although technology optimization has always shown benefits, organizations must not underplay people optimization. Typically, a practical optimization framework involves proper planning, operational preparation, organized deployment, and ongoing performance measurement. However, the right technology coupled with the right people delivers the best possible value to the business. After all, data scientists are not cheap, and 80% of their time spent on data wrangling can’t be the optimal usage of their skills. Data Modernization helps minimize the ‘Cost of Insights’ by enabling faster, cheaper, better, and powerful self-service.
Next, we must understand that data tools are used by people with varying degrees of analytics expertise at all levels of the organization. While some might only need intermediate BI capabilities, expert users require sophisticated tools to perform advanced activities. For example, polyglot programming — where a team with varying language skills may work together, or one developer may work in multiple languages to capture additional functionality and efficiency. As different personas have different needs, businesses should be free to use what they want, not what IT mandates, while providing access. Hence, a modern data ecosystem makes it simpler to align with users’ requirements, thus improving the ‘Ease of Use of Insights.’
And lastly, there is ‘Business Value of Insights’ The ultimate goal of having cutting-edge data infrastructure is to extract business value from a surfeit of information. Organizations want to leverage their data to become more efficient, reduce risks, save costs, improve customer satisfaction, and open up unexplored growth areas. Insight-rich enterprises have always been the flag bearers in initiatives like monetization, commercialization, new market-new product development, or even reimagining old products for the digital era. A modernized data ecosystem empowers organizations to orchestrate their data initiatives better, shift from ‘Data-Driven’ to ‘Data as an Asset,’ and make smarter decisions to drive business growth and stay ahead of the curve.
Key Drivers for Data Ecosystem Modernization
The ‘Known Unknown’
Most of the traditional businesses aspire to become the next Uber, Netflix, Airbnb, Alibaba, or Amazon. But, in their exponentially growing data, the landscape becomes highly complex, operating in silos, and dotted with independent point solutions. And, there’s a good chance they are not even aware of how much data is being leveraged by their business units. Although the companies may be sitting on a massive volume of disparate dark data, there is a lack of synchronized effort for business value realization. Businesses are unknown of their data’s known potential; and how they could use this asset to boost efficiency, reduce expenses, or predict customer behavior, ad-hoc maintenance, or the extent to which an upcoming campaign will be a success. There is just so much value to be gained, and so much we are already missing out.
The Cloud Adoption
Cloud is the perfect platform where data gains scale, agility, and the power to drive reinvention. Most of the data analytics tools used throughout the data value chain are available on the cloud. Also, all the major Cloud Service Providers (CSPs) are investing to develop new capabilities. Hence to handle a large volume and variety of data, businesses must modernize their data ecosystem that is either built on the cloud or compatible with tools on the cloud. Also, cloud platforms offer to ingest data from disparate sources — both external and internal — at a scale and cost that makes for the perfect ROI. Cloud-native tools for advanced analytics, AI, and automation adapt to the data on the cloud and make it work — one less headache for organizations. A modern data foundation built on the cloud provides the optimum storage, compute, warehouse and security to drive business outcomes.
Data Democratization
Data democratization enables organizations to re-imagine data in terms of managing, distributing, and interpreting. It dictates that data is available to and used by relevant people and programs, its value is unlocked. Its objective is to enable teams or individuals to use data at their convenience, where possible, without the need for expert assistance. And, to build enterprise-level data democratization, it is vital to package data the right way to encourage its consumption. For example, data services as APIs or microservice may facilitate plug-n-play technologies for ‘non-technical business users. Another way to boost consumption is to illustrate data-heavy information in infographics or interactive reports. Also, technologies like conversational AI and augmented reality make human-to-machine interactions exciting and straightforward. And, data ecosystem modernization has always been the key enabler to create unique ways of creating and capturing data. It not only makes capturing large volumes of information possible but also converts raw data into a meaningful format that encourages consumption.
Data Quality and Security
Another key driver for adopting data ecosystem modernization is to improve data quality and security. Data drives strategic decisions and hence must be trustworthy along with the right level of authorization. Often, persona-based digitization of the certification process in real-time, and its frequent audit, have been the common challenges. And, this is primarily due to ever-increasing volumes of real-time data in the form of structured, semi-structured, or unstructured. Also, the quality, cleanliness of masters, adherence to privacy, security, and regulatory norms, and records of the data lifecycle with tracking and lineage further improve the trustworthiness of the data.
How Do You Evolve Your Ecosystem?
Three steps to modernize your data ecosystem:
Assess & Strategize:
- Set up a dedicated data office to enable data democratization. The data office will be responsible for overall data strategy, design, operations, governance, quality management, privacy, and protection.
- Assess the current state by benchmarking current maturity in capabilities to capture, process, and analyze data. This process must cover technology, people as well as methods
- Determine the NORTH STAR. Map out your framework of sharing data internally and externally. Envision your “target state” and identify critical activities in achieving it.
- Develop a strategic roadmap to deliver continuous value over the lifespan of your modern platform.
- Layout the ‘to-be’ architecture that is robust, scalable, and technology agnostic. Lock in your CSP and SI, more like your strategic partner than a technology vendor.
- Establish the right platform for business experts to collaborate with the data and analytics experts. Remember, this transformation would require leadership commitment from the top of an organization.
Migrate, Modernize, Operate, Optimize (M2O2)
- Take this opportunity to hit reset on your legacy infrastructure and remove any technical debt.
- Secure the organization’s data and modernize it while migrating safely without any business disruptions.
- Stand up cloud services, build data foundation, migrate, as needed, from on-prem, build new data products.
- Empower business SMEs to create sophisticated data pipelines and provide tools to connect various cloud, on-premises, hybrid software applications, and data sources
- Create a virtual and integrated view of data in-memory and centralize administration while improving scalability and reducing workloads
- Develop a strategy to modernize BI that obtains a 360 view of the business by eliminating the data silos and delivering actionable, timely, accurate insights
- Use automation to drive simplicity, consistency and reduce your Time To Value.
Futuristic Mindset
- Focus on big tickets items with maximum potential for increasing revenue, improving profitability, and mitigating risk.
- Evangelize acquiring analytics skills and the skills to create a data-driven culture fueled by analytics. That involves creating an immersive analytics environment based on the modernized system. Data value realization through information visualization, visual analytics, virtual and augmented reality, and intuitive user interfaces.
- Think about how your AI use cases can scale and how different business units can onboard AI.
- Identify the fundamental business challenges you are trying to achieve or would like to address in the coming future. Focus on achieving it by establishing the proper governance around your operating model.
- Cloud and digital capabilities give access to a future with much more significant opportunities. Dare to go big and look for applying AI/ML, HPC even if you are small.
The onslaught of digital is worrisome and exciting. Worrying if you are ignorant about what data you are aware of and unaware of. This would mean missed opportunities in terms of revenue, expenses, or market share. However, new data can be exciting, too, if you can fully utilize the new data value chain. So, data’s worth depends on its usage and application. It does not matter how much data you are exposed to if you cannot use it at the speed of your business.
Are You Ready to Evolve Your Data Ecosystem?
It is a strategic imperative to modernize the data ecosystem to harness the real power of data. A next-gen, robust, scalable, and fast data foundation is the key for the customers, suppliers, and employees to collaborate and operate with data at their fingertips. Furthermore, it enables human ingenuity, enriches customer relationships, taps into new markets, and competes with disruptive business models. In short, modernizing your data ecosystem and running your data, associated processes, and consumption workloads on a next-gen digital platform is the key to transforming your business to grow, innovate and generate sustainable value.
Want to have a quick conversation with one of our data experts?
Schedule Now
Featured Insights
The Promise of Moving from Legacy to Modern Data Systems
Data Intelligence Summit Nov 2021 (Video) Keynote by Joe Caserta, CEO.
Overcoming the #1 Inhibitor to a Successful Data Ecosystem Modernization Effort
Data Intelligence Summit Nov 2021 (Video) by Aileen Blass, Caserta Data Strategist.
Client Success: Alan Clarke from Flutter International | Poker Stars
Data Intelligence Summit Nov 2021 (Video) Client Keynote by Alan Clarke, Chief Client Officer, Flutter International | Poker Stars.
Keynote Address (Video)
TDWI 2021 Keynote: “Migrating to Cloud Data Platforms” by Joe Caserta, CEO.
Blog Post
Quickly deliver high quality data-as-product widgets at scale
By Daniel Block, Chief Architect at Caserta
On-Demand Webinar
Elevating the 360 view of your customer: How IT and marketing make it happen—together
Our industry-leading clients trust us to help extract value from data.
Publishing Giant Transformed Into Data-Driven Marketer
This 167-year-old publishing giant collaborated with Caserta to bring them to the future by completely reengineering their legacy data ecosystem to the cloud—all on a tight deadline.
Midwest Investment Migrates to the Cloud
Harnessing Caserta’s expertise in cloud architecture and enterprise data analytics, this leading midwestern investment firm moved to the cloud to able to leverage internal data assets and ingest and analyze new, real-time alternative data sources to deliver high-value investment results to its clients.
National Non-Profit Employs Cloud-base Advanced Analytics to Improve Marketing Efficiency
With the goal of reaching a growth target of 50 million members by 2020, this non-profit sought to transition to a digital-focused company with the dual-goals of improving the overall member experience to increase member retention, while also improving marketing efficiency across all channels to increase new member acquisition.
Their solution architects are exceptionally knowledgeable about this space. They made a commitment and did whatever it took to deliver on their promises. Their work ethic and deep knowledge of data warehousing really stood out. Their solutions architect was fantastic, easy to work with, and great at explaining new technology to the business. I was very pleased with them.
Chief Information Officer
Non-Profit Healthcare Organization
Learn how Caserta can help you.
Here’s how Caserta helps you extract value from data.
Strategic Technology Consulting
Every business is different. Perhaps your organization is struggling to be completely in the cloud or maybe you’re looking for multi-touch attribution driven by Machine Learning to give your company an edge over the competition. Caserta understands each clients’ unique challenges and gives the right answers to make change happen.
Advanced Technical Implementation
You are a tech ninja, but your company has limited time and resources. Caserta expands your core team to ensure a faster and more successful project. We delve into your business to understand your unique technology stack and needs and deliver the best way to take your business further.
Certified Technology Consultants
You need to focus on building your business and pushing the needle; not on sourcing and bolting together the latest tech. Our certified technology consultants are sensitive to the unique needs of your business so you can enjoy a smooth cloud transition while focusing on what you do best.
Step 1
SCHEDULE A DISCOVERY CALL
Step 2
CLARIFY YOUR SCOPE OF WORK AND STRATEGY
Step 3
LAUNCH OR RELAUNCH YOUR MISSION
Consultations are free.
Let’s discuss your roadmap to success for your data and analytics project. We would love to hear about your goals and challenges. If we find an opportunity to work together, then we can discuss next steps. If not, we’ll gladly point you in the right direction.