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.
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.
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.
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.
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 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.
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.
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.
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.
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