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How Big Data impacts Digital Transformation strategies

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Big data plays a pivotal role in digital transformation success

In today’s time, data is the key in every organization’s success. Companies are ruling on the basis of successful big data tools one has. The enormous amount of data that is generated every day, needs organized and systemic collection system. As majority of the organizations have explored innovative technologies domain, thus, digital transformation services gets huge momentum to boost.

Although the idea of digital transformations seems very appealing but a proper methodology is needed to digitize the firm. How the data will collected, researched and analyzed needs successful path. Here we will check out the execution of big in digital transformation happens.

Artificial intelligence for digital transformation through big data

As with every passing day, artificial intelligence technologies are becoming more powerful, thus there is denying that is one of the frontiers in making transitions in data industry of today. There is an increase in customers’ demands and organizations are trying to overcome the demands by building new models with artificial intelligence to have better engagement. Digital transformation with artificial intelligence happens due to constant upgrading of smart insights with data generated through big data. Big data is used as a leverage factor by many organizations to improve their data operations through artificial intelligence. With help of data through customer engagement the digital transformation will help in shaping better analytical insights.

IoT helps in digital transformation

Internet of things is one the young and new technological concepts that is data driven, and can generate huge data via different device transmissions. The technology of Iot sits upon models of deep learning and machine learning which accumulates for huge statistics of data to create datasets. Thus, digital transformation gets help from IoT.

Automation helps big data with transformation in digital platform

With gradual rise of the automation, many services that earlier required the manual skill can now be done in a click through data models. The large amount of automation generates a lot of data which in return gives scopes to the companies to engage humans through data transformation. This is a boon in disguise as the large amount of data get organized through digital handling.

The digital transformation has come in handy at a very crucial point. It helps in maintaining the records of customers and clients in an organized methodology with getting erased. The artificial intelligence works hand in hand with digital transformation to retrieve back any data lost in keep track of clients and customers. The sectors that have got the major boost are banking, healthcare, finance and insurance. The bridge between AI and big data has helped in improving performance in these sectors.

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How technology advancements help in digital transformation for global industries
digital transformation

How technology advancements help in digital transformation for global industries

Organizations that triumphantly executed digital transformation have seen faster growth in their industries in comparison to their competitors. Surely, this process varies for each domain, business, industry, organization and their relative peculiarities. The right solutions are always achieved depending on the behaviour of a customer, preferences, analysis and different business logics of a company. The

Not so long ago experts were proclaiming that the mobile is going to be the future. And, guess what? They were not wrong. Some of the extraordinarily successful applications and businesses are mobile-based. Just think of the names like Instagram, Uber, Swiggy. Didn’t they transform the thoughts of a human into exceptionally well-crafted businesses and apps? Yes! They did. And for all those successfully running transformations there has been a secret that we need to know. That is, how they bridged all those gaps between a human and a machine and made a remarkable equation. How did they master it? Rapid Changes need adaptability With evolving technology, humans started to find a solution to every problem they encountered and started converting that as key thought of a business. Now, devices and machines are understanding from a deeper level than that of a human. Just think about all the technologies used in health care? How we have transformed from checking pulse with a finger on the wrist to having an oximeter for accuracy? There was take-away of food while we were kids and now food to your doorstep with a click. From buying a ticket at the station to booking it on the app. With changing needs and adapting new trends there has been a good equation we need to learn between a human and a machine. How do machines learn? Artificial Intelligence and machine learning happen basically in four types. This is exactly how the data is processed, observed, corrected and output is obtained. The key techniques in which the ML or AI leveraged to learn are as follows • Active Learning: Generally the models incorporated in machine learning are to guess the solution, check if it correct and go ahead to solve a similar problem. Active learning is a similar kind of work that AI and ML do. They take prioritized mathematical techniques from the subject matter expert and follow them to derive results. This method improves a positive collaboration between a human and a machine. • Transfer Learning: In this technique, the neutral network is well trained to solve a particular type of problem. Then the knowledge acquired in solving that problem is now transferred to apply for another different model but a similar kind of issue. For example, a problem solved in recognizing a car is relatively transferred for similar issues related to identifying a truck • Reinforcement Learning: This technique is used as a trial and error method. Where the successful methods are rewarded as right moves and the error methods are considered to recheck the process. This is mostly done by AI agent and is taught successful strategies. Through the process, the AI understands how well it can make the right choice to avoid consequences without any explicit instructions from the programmer. • Meta-Learning: This technique is a subfield of machine learning. It is programmed with certain types of algorithms that can teach a machine how to absorb the data. Simply how to learn what to learn. This helps the machine to upgrade in the form of skills and environments without the necessity of loading huge datasets. How should a human learn? This question might surely sound surprising. But, to have a great equation with a machine, humans need to upgrade on few things and learn a few. • Team game: Forming a potential team that is skilful in upcoming trends helps to work as a better team with those having skills in the current trends. This collaboration can bring out results that are meeting the current needs of a business and are also braced to encounter the new demands. • Discover: There is never s straight line to great innovations. Sometimes the non-linear process of going two steps back can bring out great ideas that can create wonders. • Test: Learning is always a process that goes on forever. It becomes successful only when tested and then identified as the right way. So a successful project gives a lot of skill enough to embrace another one. • Fail: The most common of all. It helps in a way better than a successful project. It gives clear guidance on what not to do. And, when it happens, stand again to start again. • Lead: Ensure everyone on the team is coached and trained to take over the project at any given time and circumstance. Throughout the process of a project, situations keep on changing and one needs to be well informed to face anything. • Unlearn and upskill: Every time a new problem arrives, the same process that succeeded in the previous issue might be completely irrelevant to this one. So be open to unlearn outdated processes and upskill to the emerging solutions. Conclusion From observing new technologies and how they are transforming digitally, it is very much evident that not just machines, but humans have a lot to learn to form a great equation. A good partnership between humans and machines can only be achieved if machines are made with accurate tools and technologies, and humans who can embrace diversity, nurture it across the industries and their ecosystems.
digital transformation

Understanding equations between humans and machines to master digital transformation

Not so long ago experts were proclaiming that the mobile is going to be the future. And, guess what? They were not wrong. Some of the extraordinarily successful applications and businesses are mobile-based. Just think of the names like Instagram, Uber. Didn’t they transform the thoughts of a human into exceptionally well-crafted businesses and apps?

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