DATA=KNOWLEDGE=POWER=PROFIT
DATA AND AN ANALYTICS ARE KEY TO BEING COMPETITIVE AND AGILITY
INTRODUCTION
Nowadays, data is called oil. Data-driven market. Data is power. Why does data become so valuable?
The explanation is: ?Data has become one of the most valuable resources or assets enabling immense benefits for any organization irrespective of their sector and sphere. Acknowledging the value of data is of utmost priority in this digital world. Data is central to every digital transformation. But not all data is in a state that is acceptable to be used for productive purposes – in fact, only a few organizations have data that meets up with basic quality standards and can be used reliably by the new technologies they are implementing. Handling data properly requires continuing to work with it is very important to assure that it remains valuable and doesn’t collapse digital transformation before it can start to pay off. Data is to a digital company as blood as to the human body: you might not think about it much, but it’s still there in the background, keeping everything going. The most promising aspects of digitization require extensive amounts of good quality data in order to function at their best.
The?combination of processes and operations, greater teamwork across departments, increased agility, and data-driven intuitions, can be used for improving customer experiences and cost savings through greater proficiencies. Unlocking of data has now become a key priority and thrust area for an organization head. It is already proved that an organization’s adoption of technologies and processes that optimize data innovation is correlated to business benefits like leveraging data to increase revenue and lowering costs.
Data management technologies, practices, and processes used to unlock the Value of Data with Data Innovation Acceleration tools. Now technology advancement in organizations remains to bring about more data in new and different ways from the propagation of edge and IoT devices, which became past by new application monitoring and observability streams, to exploding customer data generated from new digital services and experiences. Organizations look toward a mandate to leverage their wealth of data to the benefit of the business as opposed to leaving it an untapped resource.
?The method of creating of structure for a mature data innovation practice that can unlock the value of data is many-sided. It requires a comprehensive view of high-quality data and technologies that can scale and keep pace with vast and accelerating data generation. It also requires cross-functional collaboration with technology teams in sync with and effectively supporting the organization’s “data disruptors” like analytics teams, developers, and data scientists. The above questions are lead to a maturity characteristic: a behavior or technology in use that identifies the organization as a leader.
ENTERPRISE STRATEGY GROUP (ESG)
?ESG’s proposition was that organizations with more Data Innovation Maturity would significantly outperform their peers in terms of their ability to drive business transformation with data. Like the inclusiveness of their data integration, the quality of their data (i.e., its accuracy and veracity), the quality of collaboration between IT and data users throughout project lifecycles, the adoption of technologies like artificial intelligence and machine learning to support, automate, and scale data management operations in order to analyze organizations by their ability to partake of, organize, and analyze their data. As any volume of data has no value it is not properly arranged, structured, and able for analysis to provide the information we desire. ?Enterprise Strategy Group (ESG) is an integrated technology analysis, research, and strategy firm providing market intelligence, actionable insight, and go-to-market content services to the global technology community. It is increasingly recognized as one of the world’s leading analyst firms in helping technology vendors make strategic decisions across their go-to-market programs through factual, peer-based research. ESG is a division of TechTarget, Inc. (Nasdaq: TTGT), the global leader in purchase intent-driven marketing and sales services focused on delivering business impact for enterprise technology companies.
DATA INNOVATION ACCELERATION/ACCELERATOR
Segmenting the Market in terms of Data Innovation Maturity back to Contents Cracking the Value of Data with Data Innovation Acceleration are showing that most organizations are besieged with a fragmented view of their imperfect data, don’t have the technologies in place to keep pace with their data, and are clashing with infighting among teams, just?some organizations meet the verge of operating an Accelerated Data Innovation practice. There is a clear imperative for most organizations to totally evolve how they approach data management today in order to maximize the return on their data capital.
An organization can reap the benefit if decisions are based on data making a major successful strategy adjustment, abridged organizational risk enabled development of new product, service or revenue stream, lower cost of business operations, improved regulatory compliance, increased employee efficiency/productivity, enhanced customer service/experience, upgraded IT/application availability/predictability, and improved product or service quality. It is not surprising to note that more mature organizations have seen the greatest return over the past year from their data management efforts: Data Innovation Accelerators credit their data management practice with improving customer experience, ?increasing employee productivity, improving product quality, improving application availability, improving compliance, reducing the cost of operations, and reducing risk. Data Management Returns increased with Data Innovation Maturity over to past years. Data management practice has made a major successful strategy. It enabled the development of the new product, service, or revenue stream, reduced organizational risk, lowered the cost of business operations, enhanced regulatory compliance, Better-quality IT/application availability/predictability, Better product or service quality, Augmented employee efficiency/productivity, and made best customer service/experience.
?One of the key areas to which organizations are applying their data management insight is cost optimization. Through better data management, organizations are better equipped to find waste and superfluity in business processes, more efficiently assign skills and resources where they will have the greatest return, and sidestep costly mistakes caused by deficient data and analysis. The financial consequences are clear, but Accelerators are also positioned to be better corporate citizens through improved corporate sustainability. Accelerators’ ability to reduce waste has a social, environmental, and cultural influence that goes well beyond optimizing financial results for the business.?Better analysis of data can help organizations identify market opportunities and get ahead and respond to changing customer likings more swiftly to make what customers require in real-time. Not only are more mature organizations launching more products per year than less mature organizations, but they get these products to market ahead of competitors more often.
Data Innovation Accelerators’ superior ability to interpret, understand and react to market demands fuels innovation. In turn, these organizations optimize the customer experience. As noted earlier, improved customer experience is the benefit most frequently cited by organizations as being driven by their data management practices. Organizations have the prospect to use data from employees’ everyday work to identify outlines that bear productivity and engagement, providing employers with actionable insights into key areas of improvement.
This can create challenges with application monitoring and observability. Organizations must increasingly apply advanced data management and analytics capabilities in order to effectively measure performance, availability, and user experience. Our research shows that organizations with high Data Innovation Maturity are better operationalizing application data to maximize uptime. At many organizations, it means vividly changing how data assets are acknowledged and garnered, curated and consolidated, and analyzed. Clearly, the business payout of this work is significant, but not all IT organizations and leaders are goals based on business outcomes.
DELL TECHNOLOGIES AND INTEL
Dell Technologies is among the world’s leading technology companies, instrumental in developing solutions to help transform people’s lives with extraordinary capabilities. The company brings the infrastructure, tools, and processes that help organizations create modern data conduits across and between on-premises, edge, and public clouds, rapidly reducing the time between data creation and modernization to help an organization prevail over unexpected impediments and grasp unexpected opportunities - all personalized to the way required to attain and ingest IT. Dell Technologies will stop at nothing to help an organization harness the transformative power of technology so it can be ready for whatever comes next. ProSupport Plus services to maximize productivity which streaming Data Platform comes with Dell Technologies ProSupport Plus, providing proactive and predictive support to get ahead of problems before they happen. Accelerate time to value with Dell Technologies deployment and consulting services that are tailored to meet your needs, from planning and design through implementation.
?Jointly ?Intel and Dell Technologies are driving innovation and next-generation capabilities with the broadest portfolio of trusted client and enterprise solutions for cloud and data management, enabling businesses to move faster, innovate more and operate efficiently VMware’s cloud, app modernization, networking, security, and digital workspace platforms form a flexible, consistent digital foundation on which to build, run, manage, connect, and protect data and applications, anywhere. Dell Technologies aligns the unique advantages of VMware software with Dell's synergies to deliver even more value to customers by providing the essential infrastructure to revolutionize with data, shape their customers’ digital future, and renovate IT.
?SOME USEFUL TECHNOLOGIES ANALYZING DATA MORE PROFICIENTLY ARE AS FOLLOWS:
?1.??5G is set to be the next generation of network connectivity and will transform the way we live, work and play. 5G will power a world of connectivity, enabling mixed reality experiences where the physical and digital worlds converge. As the very first mobile infrastructure built in the cloud era, 5G will be an indispensable part of our data-driven future.?It has the ability to unlock the value of data in unprecedented ways.
?2.??Thriving in the digital world means you'll need to rethink where, when and how you generate, manage and act on data. Here are three ways to meet the new data-centric standard.
?3.???Some ways to realize new value from your data: Leverage your data wherever it lives, modernize infrastructure and improve connectivity by extending cloud benefits to the edge, optimize the flow of data, simplify and standardize how data moves across your organization to accelerate insights, create compelling customer experiences, and modernize innovation process to iterate and deliver ongoing customer value.
?4.??Data science real-time business insights with streaming data at the edge
The Dell Streaming Data Platform is a platform for ingesting, storing, and analyzing continuously streaming data in real-time. By combining this streaming storage solution with the convenience of out-of-the-box support, Data streaming in from the edge continues to grow exponentially. With the influx of devices like security cameras, drones, and mobile apps, even the most established organizations can feel like they are bursting at the seams. With this massive influx of data, it is time to begin, or re-structure, your organizations’ digital journey - re-evaluating your infrastructure to harness the business insights available through the analysis of real-time data.
? 5.??Enterprise-ready platform gives organizations access to a single solution for all of their data (whether streaming or not) that provides out-of-the-box functionality and support for high-speed data ingestion with an open-source and auto-scaling streaming storage solution. The offering is built on open source technologies – such as Apache Flink, Spark, and Pravega – and with connectors to applications such as Boomi and Kafka - to enable accessibility to a large array of capabilities and engines. With a programming model that empowers the capabilities of multiple engines.
? 6.??SDP helps to reduce application development time, giving your team more time to focus on ingenuity and the next level of business needs. And as a buildable platform, SDP empowers multiple options for underlying stream processing engines and connected applications, providing flexibility for any organization to derive real-time business insights as data is ingested and eliminating storage and operational inefficiencies.
SOME IMPORTANT?TERMINOLOGIES:
Unified: One single platform to unite real-time, batch, and historical analytics for improved storage and operational efficiency.
MODERN: Turn-key modernization built on open-source components with platform options that provide future extensibility for unlimited scale.
TRUSTED: As an out-of-the-box platform, experts are at your fingertips for planning, design, implementation, and support, all with a technical expert. Experience real-time business insights with streaming data at the edge, and High-speed and Ultra Scalable Results
??DELL STREAMING DATA PLATFORM
By ingesting all data as a stream, the Dell Streaming Data Platform can ingest, analyze and store massively fluctuating volumes of data with ease. Because the platform is built on Kubernetes, storing all that data is just a matter of adding nodes. Now that you have all that data, using it becomes a practice in innovation. By auto-tiering storage upon ingestion, SDP allows for unlimited historical data retrieval for analysis alongside real-time streaming data - enabling endless business insights at your fingertips, far into the future. The Streaming Data Platform helped a construction company ensure that their project was on time, accurate, and machinery was optimally allocated.
SDP ARCHITECTURE AND CONFIGURATION WHITEPAPER
The solution components, logical and physical infrastructure, configuration details, and considerations to make when selecting and deploying a solution. It helps store, manages, and protects unstructured data with efficiency and massive scalability
?THE ROLE OF DATA IN DIGITAL TRANSFORMATION
A digital transformation project can not be efficacious if a comprehensive and holistic tactic and digital transformation plan are applied from the beginning. Transformation encompasses all processes, interactions, and transactions, besides a multitude of internal and external aspects exceptional to an organization. Get it right, and the benefits are plentiful, including the consolidation of processes and operations, greater collaboration across departments, increased agility, and data-driven insights, which will result in improved customer experiences and cost savings through greater efficiencies.
Digital transformation provides businesses with real-time information and greater visibility into operations, particularly when it comes to the performance of people and assets. Armed with this data, organizations can gain an exact consideration of surely who their customers are and how they behave, as well as enable them to identify trends, impact change, and make the essential and instant enhancements that will determine efficiencies and prune costs.
领英推荐
Data is at the heart of the digital government transformation. Gartner rightly said the transition to digital government requires careful planning of a digital transformation strategy and a focus on outcomes. To be successful, government CIOs must guide the digital journey, tackling both the strategic and tactical challenges with a relentless focus on using and sharing data to make government services more proactive in identifying and preventing potential problems, and its operations more competent.
?LIVE EXAMPLE OF DATA IN ACTION
The transportation industry has experienced transformative change within the area of data in recent times, with the introduction of onboard sensors, data collection points, vehicle location, ticketing, fare collection, and scheduling management systems.?Northern Ireland’s largest public transport provider Trans link?catering around 1 billion bus and rail passenger journeys each year. Translink, with its vision ‘To be your first choice for travel in Northern Ireland’, partnered with Version 1 to increase the highest value from the massive amounts of data seized from these different sources. Within 10 weeks of working with Translink, Version 1 technologically advanced a modern data platform using software from the?Microsoft technology stack. This simplification of the process of analyzing data across Translink’s entire domain permits its employees to drive efficiencies and add value to its business and customers.?The outcomes were remarkable, as ?Translink announced a 95 percent decrease in data report homework time and an intensely improved customer experience.
It is pertinent to mention here that Paul McGrattan,?Information & Technology Manager at Translink, declared: Engaging with a highly-skilled and collaborative Version 1 team and leveraging their expertise in the Data and Analytics space, we were able to implement – within 10 weeks – a Microsoft analytics solution that covered multiple areas of our business. This is a significant first step towards our ambition to become a modern data-driven transport organization.
?Machine learning is a famous new technology that provides all types of new prospects?to the business world. Systems and software that are equipped with machine learning capabilities can perform certain tasks (such as product development or customer service) without following a rigid set of programmed instructions. Instead, they learn how to accomplish the goals they’ve been given using a set of historical data to develop an understanding of how that process usually goes and which actions lead to which outcomes. By absorbing these examples, they are able to learn from the past experiences of others and piece together an optimal solution to the problem in front of them. Digital technologies like these depend on having access to data that can act as a kind of stored memory for them.
In short, data is knowledge, and knowledge is power; businesses that have undergone a digital transformation will never be able to flourish properly without it.
Why Having a Data Strategy Is Key
Understanding that you need data to run your digital operations properly is a good start, but not just any kind of data will do. In order to get the best results, you’ll need complete and coherent data points that you can easily compare against each other. To do this, you’ll have to think about both of the two main types of data: existing and new.
New data is the information that will be coming in after you’ve made your digital transition. In addition to adding to your records for future reference, it will provide feedback on how your company is doing in its newly digitized state. It will be the first place you will see any shifts resulting from changes you have made, allowing you to optimize your operations in a much smaller window of time than would otherwise be possible. By setting strict standards for what incoming data should look like before it actually enters your systems, you should be able to ensure that you start out with a good quality dataset.
Existing data, on the other hand, is a very different prospect. It is equally valuable as new data – if not more so – because it provides a frame of reference for what your company once was and how you were performing at that time. It also gives you the contact information of your existing client base, many of whom are likely to buy from you again at some point. However, this data also tends to be more difficult to deal with than new data because it was often collected before proper standards were put into place. For example, you might have some records with the customer’s last name listed first and others with it listed last, and even some with no customer name listed at all.
A computerized system would have trouble figuring out how to handle all of those instances and still deliver reliable, consistent analytics, which is why you can’t cross your fingers and hope that that happens. You need to actively intervene and get your data in order before you can hope for good performance from those systems.
?Companies already seeing 20 percent of their earnings before interest and taxes (EBIT) contributed by artificial intelligence (AI) are more probable to engross in data practices?that reinforce these features:
.1.???Data is embedded in every decision, interaction, and process.
2.???Data is processed and delivered in real-time.
3.???Flexible data stores enable integrated, ready-to-use data.
4.????Data operating model treats data as a product.
5.????The chief data officer’s role is expanded to generate value.
6.?????Data-ecosystem memberships are the norm.
7.?????Data management is prioritized and automated for privacy, security, and resiliency
THE LIKELY FEATURES ?BY?2025
?1.??Vast networks of connected devices gather and transmit data and time. How data is generated, processed, analyzed, and visualized for end-users is dramatically transformed by new and more ubiquitous technologies, such as kappa or lambda architectures for real-time analysis, leading to faster and more powerful insights. Even the most sophisticated advanced analytics are reasonably available to all organizations as the cost of cloud computing continues to decline and more powerful “in-memory” data tools come online (for example, Redis, Memcached). Altogether, this enables many more advanced use cases for delivering insights to customers, employees, and partners.
?2.????Data practitioners increasingly leverage an array of database types—including time-series databases, graph databases, and NoSQL databases—enabling more flexible ways of organizing data. This allows teams to query and understand relationships between unstructured and semi-structured data easier and faster, which accelerates the development of new AI-driven capabilities and the discovery of new relationships in the data to drive innovation. Combining these flexible data stores with advances in real-time technology and architecture also enables organizations to develop data products, such as ”customer 360” data platforms and digital twins—real-time-enabled data models of physical entities (such as a manufacturing facility, supply, or even the human body). This enables sophisticated simulations and what-if scenarios using traditional machine learning capabilities or more advanced techniques such as reinforcement learning.
?3.???Data assets are organized and supported as products, regardless of whether they’re used by internal teams or external customers. These data products have dedicated teams, or “squads,” aligned against them to embed data security, evolve data engineering (for example, to transform data or continuously integrate new sources of data), and implement self-service access and analytics tools. Data products continuously evolve in an agile manner to meet the needs of consumers, leveraging DataOps??(DevOps for data) and?continuous integration and delivery process and tools. Altogether, these products provide data solutions that can more easily and repeatedly be used to meet various business challenges and reduce the time and cost of delivering new AI-driven capabilities.
?4.???CDOs and their teams function as a business unit with profit-and-loss responsibilities. The unit, in partnership with business teams, is responsible for ideating new ways to use data, developing a holistic enterprise data strategy (and embedding it as part of a business strategy), and incubating new sources of revenue by monetizing data services and data sharing.
?5.??Large, complex organizations use data-sharing platforms to facilitate collaboration on data-driven projects, both within and between organizations. Data-driven companies actively participate in a data economy that facilitates the pooling of data to create more valuable insights for all members. Data marketplaces enable the exchange, sharing, and supplementation of data, ultimately empowering companies to build truly unique and proprietary data products and gain insights from them. Altogether, barriers to the exchange and combining of data are greatly reduced, bringing together various data sources in such a way that the value generated is much greater than the sum of its parts.
?6.???Organizational mindsets have fully shifted toward treating data privacy, ethics, and security as areas of required competency, driven by evolving regulatory expectations such as the Virginia Consumer Data Protection Act (VCDPA), General Data Protection Regulation (GDPR), and California Consumer Privacy Act (CCPA); increasing consumer awareness of their data rights; and the increasingly high stakes of security incidents. Self-service provisioning portals manage and automate data provisioning using predefined “scripts” to safely and securely provide users with access to data in near real-time, greatly improving user productivity.
Automated, near-constant backup procedures ensure data resiliency; faster recovery procedures rapidly establish and recover the “last good copy” of data in a fraction of time, so lessening risks when technological glitches occur. AI tools become available to more effectively manage data—for example, by automating the identification, correction, and remediation of data-quality issues. Altogether, these efforts enable organizations to build greater trust in both the data and how it’s managed, ultimately accelerating the adoption of new data-driven services.
CONCLUSION
In near future, only those organizations survive who understand the power of data. Now the ecosystem of data-based decision-making will become the order of the day.