Data Fabric is shaping a new future
Ashutosh K.
Ex banker, Now self-employed, MD &CEO of Kumar Group of companies, Author of many books.
Data fabrics is a new term that emerged but has very strong potential for a positive result?
Revolutionary innovations, brilliant ideas, and climate imperatives will change everything—except the fundamentals of finance. ?The definition of transformation has evolved over the years. In the background above, there is a historic development between McKinsey and Caserta in which the primary party announcement about having come to have obtained ?Caserta, a pioneer in data architecture and engineering on 1st June 2022. The above acquisition has been made to enhance and strengthen data capabilities and develop its clients’ leading technology impact partner, boosting work in?data strategy and design which will pave the way for its journey to be known as the global top impact partner for technology. They believe that this acquisition will make a substantial opportunity to help clients to address the hurdles in building a competitive, industry-leading enterprise data ecosystem.?
The above acquisition is a result of joint collaboration for more than decades with Caserta which built its internal knowledge management platform. They were also in collaboration after a client solicited Caserta to bring its data assets to the cloud. Just last year, they jointly aided financial services, and clients, launching a new business offering data and analytics software to a new market. Much before the end of the month, Caserta organized betterment in efficient performance and provided strong stability of their cloud-based data infrastructure, upgraded the pace at which new features could be launched, and began coaching and developing the client’s engineering team. It is termed the data-driven enterprise of 2025 in which exponential technology advances, the recognized value of data, and increasing data literacy are changing what it means to be “data-driven.” This collaboration demonstrated how well-matched both organizations are and how powerful their complementary skills are. It is made a beginning of an official relationship, and Caserta’s almost 50-person team of data engineers, data architects, and data strategists into our firm. Caserta will be fully aligned to their Data Transformation practice to focus its work on the highest impact transformation opportunities across sectors.
?Founded in 2001 by Joe Caserta, considered a visionary and pioneer in the data-engineering space, Caserta has established a stellar reputation, having designed and implemented cutting-edge data architectures for many Fortune 100 companies. They have built and created cloud-native data lakes, data streaming capabilities, and pioneering thought leadership in metaverse data engineering. In one instance, they helped a leading music streaming service build out the complex cloud platform crucial to its operations. “When I formed Caserta, McKinsey was the model I used to stay laser-focused on positively impacting the goals of our clients,” says Joe. “There is nothing more exciting as a CEO of a tech consulting firm than building a business around solving uniquely complex problems, having our teams get completely immersed in issues that matter, and creatively constructing winning, actionable solutions that launch our clients into success.” Caserta has created a unique approach to solving the most complex data engineering challenges. They use a proprietary method of linking business needs into tailored data architecture designs. Therefore, this acquisition generates a significant opportunity to aid clients to address the challenges in building competitive, industry-leading enterprise data environments.
Data is an integral part to every transformation that’s happening across sectors and geographies in the next three to five years. It’s the competitive edge most firms will be creating and defending and an area where we will see the greatest innovation. The combination of McKinsey and Caserta will position it to play a pivotal role in moving industries to the next stage of technology transformation.
Caserta enhances how we can work with clients on data strategy and design. They strengthen our ability to deliver end-to-end data transformations, bringing innovative approaches, accelerators, and talent to implement cloud data architectures at the enterprise scale, all of which are core to our client's digital and analytics development. Coming together paves the way to empower to solve more comprehensive data challenges and have a significantly elevated role in advancing businesses and society with data which is the way to creatively and deliberately improve lives and businesses around the world. When the crowd isn’t necessarily wise, leaders need to recognize herd mentality as soon as it transpires—and explore the contrarian view to help break the spell. By accepting discipline and well-defined processes, innovation teams can make finance leaders their biggest allies. Absorb what it takes to unlock the big moves that really matter for exceptional performance. At the crossroads of corporate strategy and finance lies valuation to outshine at measuring and maximizing shareholder and company value.
Risks that threaten a company’s existence require unique interventions from the board. ?How to successfully source and execute a string of deals that lead to the creation of a new business by procuring. Resilience is the ability of a business to withstand, adapt, and thrive in the face of shocks that are internal and external?or both interpret the metrics underlying, the company’s performance. Boards need to ensure that management walks the talk on culture and values.?????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????????
?Gartner predicted the top strategic technology trends for the coming year will be focused on automation, security, and AI. The technicalities go deeper, of course: hyper automation and autonomic systems, increased security through the mesh and privacy-enhanced computation, generative AI, decision intelligence, and AI engineering. But the larger issues are generally familiar. One trend is very common, the use of data fabric. Data fabric’s return is both notable and important; it underscores the need for a unified view across the democratized and ever-growing landscape of technology offerings in data storage and processing. The technology-trend predictions reflect companies’ demand for process optimization and better use of available technology. The aim is that 80% of business leaders want to move to an intelligent enterprise, which is more than mere technology. It’s the people who are the differentiator – and having the ability to use a company’s data assets is key. Building an intelligent enterprise, therefore, means “…investing in a journey that pays as much attention to cultural and process changes as it does deploy new tools.”
Advances in AI engineering, frenzied automation, and total experience are just a few of the tools available, with the Data Fabric acting as that layer of accessibility. With the wealth of data technologies available for storage and processing, upskilling the workforce across each technology to analyze output means a large in front cost and time. These inherently mean the organization will struggle to get executive buy-in for key initiatives. But by creating a single layer of accessibility through data fabric, companies can accelerate ROI – and therefore buy-in — for cloud initiatives and other strategic ventures.
WHAT IS THE DATA FABRIC
?The data fabric is the predominant data-management solution across data uses, from the centralization of data assets to a single point of access for analytics and AI. The fabric is more than just a data layer but is an insights portal with numerous uses. By enhancing the data fabric to become a “shopping cart” of data and analytics assets, enterprises step into the world of the data marketplace, one in which data objects can be bought and sold figuratively or literally.
The concept of data fabric is not very old. It was coined by NetApp in 2016,?which described that it rests on five core principles: control, choice, integration, access and consistency.?
Simply put, ?the data fabric is a single layer that enables data users to collaborate and share information and value across any number of platforms, cloud or on-premises. Data Fabric Enables Companies to Overcome Technical Debt. As companies?adopt the cloud for revenue and growth, there’s a clear need to reduce technical debt. It would appear the peaking of data fabric is actually?the result?of technical debt accumulated over years of increased technology adoption, rather than the?reduction?of that debt.
Enterprise data transformations today include a multitude of technologies – and an equally dizzying number of skills needed to support those technologies. No longer are we considering the use of relational stores like MS SQL Server, Oracle, or PostgreSQL; but now we have NoSQL options like MongoDB, Cloudera, Neo4J, MarkLogic, and others. On top of this, we are adding cloud options to the stack, with AWS Redshift, GCP BigQuery, MS Synapse, Snowflake, and more. We are comparing and adopting numerous solutions of mind-boggling capabilities and thus becoming dependent on their features. Yet they can’t move everything at once to achieve value, let alone manage all those disparate resources.
Data fabric brings a single management layer to help businesses take advantage of all the value these technologies bring. This not only allows domains to continue with their own technology roadmap but also enables end-users to take advantage of what other domains have put in place. This concept then allows for a multi-layered management and governance landscape by advancing Data Mesh capabilities across an organization, where governance and transformation are pushed back and democratized at the domain level.
Effect on the Future
Centralizing the data fabric allows for the democratization of domain-level processes and data. Monolithic can’t be the answer anymore. As?Gartner notes, large-scale lift and shift is on a downward trend, and cloud-native services are on the rise for 2022. However, cloud-native service doesn’t simply remove the hurdles of an organization’s past technology adoption. Having a single point of insight and accessibility has become fundamental for organizations to achieve value from their data assets and lay a foundation for their cloud-everywhere future ?more
IBM suggested that business leaders must make Data Fabrics a Priority in 2022. Data fabrics ensure organizational-wide and on-demand access to data sets needed for efficient operations and digital transformation. The ability to visualize and process data is the most important enterprise skill, and business leaders require this. Anything without the backing of data holds no acceptance in the digital world. Just like most technological things, data, too, is bound to evolve. Amidst the increasing use for Web 3.0 technologies such as IoT, business leaders have a key responsibility – to elevate their data management practices into future-ready frameworks.
Data fabrics ?is a?quickly growing market, and enterprise decision-makers across the board are asking for it. What’s interesting is the rising adaptability of the fabric in organizing data regardless of the sector, historical landscape, or the underlying technology. It makes , the?CAGR of 23.8%?growth till 2026 doesn’t look like a hard task. So everyone involved in the process of building data teams, all C-level executives (including Information officers, Data officers, etc.), data scientists, analysts, AI developers, and the stakeholders should align the organization’s expectation from the practice called data fabrics.
??PURPOSE OF DATA FABRIC?
?It is not only a data management protocol but also dissimilar traditional practices, these extract the best from automation, thereby ensuring flexibility, accuracy, and sustainability. Therefore, data fabrics are an AI-enabled management architecture that continuously feeds analytical insights to our metadata and ultimately contributes to smarter business decision-making.?Its ability to forecast the actual usability of data sets in multiple new patterns, for new metadata types, new forms of orchestration, and drive smart reporting for – the-moment analytical consumption.?Thus, ?D&A leaders can utilize the opportunity to replace human effort (and error) by eliminating primitive data management & maintenance technologies. Human resources, at the same time, can be leveraged for more creative and critical strategic building.?Regardless of the incoming source, the fabric ensures organizational-wide and on-demand access to requested data sets.?Now, it is observed that the data fabric architecture is least impacted by the changing data environments, preferred usage policies, management processes, and others. As a result, it proficiently automates data discovery and governance initiatives while preparing enterprise-ready analytics.
?Now, the enterprise fate sways on the quality of data processes and behind the scene decision takers. It has a direct impact on the stakeholders and has to achieve targeted outcomes. Therefore, decision-makers should ensure that the practice involves everyone on the board. Make it a collaborative activity than just a few executives taking the call. At the same time, it should be:-
1) A collaboration of machine AI and human consciousness
Against popular belief, AI is not killing human jobs. It’s rather putting them for more critical (and productive) roles. Humans excel in a contextual analysis of a decision-making process, while machines are best suited for more rational problem-solving roles.
2) Adaptable to change
The decision-making should acknowledge the versatility of data. Subsequently, the finalized decision should fit in ad-hoc scenarios and thus complement the enterprise’s scalability goals in the future. If required, break the decision-making process into multiple smaller decisions. The process should be context-sensitive at every level of multiple components.?
3)?Modern challenges require modern solutions?
Data management is not new. Automation in data management is not a new practice anymore. It’s been around for more than a decade ever since the industry woke up to Big Data analytics. As we inch closer to the era of web 3.0, the rate of data production will increase exponentially. And that’s exactly why we need a super-intelligent management process to handle this mad rush with finesse. Needless to say, business leaders have an important role to adorn here. They must detach their organizational data management from primitive practices and adorn the latest technology. While we are at it, it is important to acknowledge the success of micro-databases.?
K2View Data Fabric, for example, uses micro-databases to manage data through digital entities. Capturing fragmented data sources from multiple systems in silos organizes them into an exclusive data schema wherein every schema represents a specific type of business entity. Each business entity (digital entity) is stored in a unique micro-database. For organizations, it is an efficient way to unify all information about a specific business entity while making it accessible for everyone. For business leaders, it is an opportunity to revamp their data practice into a more integrated ecosystem.?Besides updating the data in the source systems, the?fabrics are scalable and assist?millions of micro-databases parallel. As a result, there is distributed, automated, and high-performing management architecture in the bottom layer. It’s an open marketplace. Everybody has access to the latest technologies, and the sole differentiator is the ability to foresee change and act in advance. With respect to fabrics, data science leaders have a greater task in hand – to visualize, plan and prepare their organizations for a volatile digital landscape.
THE DATA FABRIC MARKET TO DEPICT A 22.3% CAGR FROM 2022 TO 2029
The global?data fabric market?size stood at USD 1.43 billion in 2021. The market is anticipated to rise from USD 1.71 billion in 2022 to USD 6.97 billion by 2029 at a 22.3% CAGR during the forecast period.?Fortune Business Insights??has deep-dived into these insights in its latest research report, titled, “Data Fabric Market Revenue,?2022-2029.”
According to an analysis, the data fabric has become sought-after to regulate data management practices and streamline cloud, premises, and edge devices. A notable shift towards the cloud will boost the trend for data fabric solutions. To illustrate, in November 2021, IBM Corporation infused funds into SingleStore to bolster its mission of unifying the cloud database.
COVID-19 Impact
Pandemic-induced Volatile Demand to Prompt Investments
Industry participants expect the COVID-19 pandemic to have a notable influence on the global landscape, with data services witnessing exponential demand. While the outbreak had a telling impact on BFSI, manufacturing, and healthcare sectors, data fabric solution providers observed a bullish demand across advanced and emerging economies.
?Segmentation
In terms of deployment, the Data Fabric Market is segmented into on-premises and cloud. Based on type, the industry is segregated into in-memory and disk-based. On the basis of enterprises, the market is fragmented into large enterprises and SMEs. With respect to application, the industry is segmented into governance, risk & compliance management, fraud detection & security management, customer experience management, business process management, sales & marketing management, and others.
In terms of end-user, the market is segmented into retail & e-commerce, government,?IT & telecom, BFSI, manufacturing, healthcare & life sciences, media & entertainment, energy & utilities, education, and others. With respect to region, the market includes North America, Asia Pacific, Europe, South America and the Middle East, and Africa.
?Drivers and Restraints
The trend for AI/ML to Usher in Innovations
Industry players expect the adoption of online platforms to boost data fabric market growth during the forecast period. According to the Data and Analytics Adoption Trends Study 2018, organizations planned to automate 49% of data integration and 37% of data preparation tools by 2020. Leading players are poised to infuse funds into sophisticated technologies to streamline data management strategies. Moreover, in June 2021, IBM Corporation rolled out IBM Cloud Pak for Data 4.0 with automation and a combination of AI lifecycle and data to offer intelligent data management tools. However, a lack of control over data and visibility to store data on the cloud could dent the industry growth.
Regional Insights
North America to Provide Promising Opportunities with Business Process Management
Stakeholders expect the U.S. and Canada to offer lucrative growth potentials with rising demand for fraud detection and security management. Prominently, the need for business process management services could further underpin North American data fabric market share. Moreover, the expanding penetration of advanced technologies will bode well for regional growth. Europe's market forecast will be strong with a growing trend for information and communication technologies, electronic devices, and networks. Digitizations will be pronounced across the U.K., France, Germany, and Russia. Large enterprises and SMEs will continue to exhibit demand for data fabric solutions over the next few years. Prominent players are poised to infuse funds into the Asia Pacific industry on the back of technological shift across China, Japan, Australia, and India. It is worth mentioning that China is behind the U.S. as the leading country in data center adoption. Notably, demand for advanced solutions will be sought across governance, risk, and compliance management applications.
COMPETITIVE LANDSCAPE
Prominent companies are slated to focus on mergers & acquisitions, product launches, technological advancements, and research & development activities. Industry players could foster penetration to bolster their geographical expansion and product offerings.
KEY INDUSTRY DEVELOPMENTS
In August 2021?– IBM Corporation announced a collaboration with Cloudera by providing Cloud Pak for Data capabilities to Cloudera Data Platform. Talend Inc. added new innovative capabilities in its fabric tools with a governance platform and integration to manage secured corporate information.
?MAJOR PLAYERS PROFILED IN THE DATA FABRIC MARKET REPORT:
?IBM Corporation (U.S.), Oracle Corporation (U.S.), Hewlett Packard Enterprise Company (U.S.), SAP SE (Germany),????????NetApp, Inc. (U.S.),?TIBCO Software Inc. (U.S.), Talend Inc. (U.S.), Informatica LLC (U.S.), Denodo Technologies Inc. (U.S.), and Neo4j, Inc. (U.S.)
?Conclusion
Though data fabric is new coined word but now its future looks very prospectus.