How will Artificial Intelligence, Data Analytics and Automation change the Future?

Business landscape is being reshaped at a rate that has never been seen before. Since the beginning of the year 2000, two-thirds of the Fortune 500 companies have gone bankrupt, merged with a different company, or been acquired. In contrast, technology-driven firms have more than quadrupled their market share in the last five years. What is the key differentiator between these companies? The answer lies in the way the successful ones have collected and used data to rapidly make informed decisions.

In today’s interconnected world, over 2.5 quintillion bytes of data is produced daily. Using such huge volumes of data to enable businesses to make profitable decisions is only possible with a combination of data analytics, artificial intelligence (AI) and automation.

Data Analytics Automation

Automation of the life cycle of data analytics using Artificial Intelligence (AI) or Machine Learning (ML) based methods leads to Data Analytics Automation. Quick insight discovery and smart decision-making are possible with data analytics automation since it allows users to monitor and analyse huge sets of data in a convenient and efficient manner.

By using AI, enterprises can quickly accelerate data construction and insight creation methods in a simplified fashion. Using AI/ML algorithms, an enormous amount of data can be analysed quickly to identify patterns and come up with insights for worthwhile actions. Businesses can be transformed with AI-enabled data analytics automation, whether it is for better customer engagement, existing product optimisation or predictive analysis of future decisions.

It is already well known that AI-enabled data analytics accelerates the organisation of data, automated insights, and report generation, leading organisations to world-class data-driven decision-making.

These are key business advantages of using automated data analytics:

  1. Quick, efficient insights for rewarding decisions
  2. Speed is essential to stay competitive for any business. Whether it is to successfully launch a new product or a service, or to unveil upgraded offerings, accurate data insights are vital. Measuring and understanding the data from various sources is always a challenge. Using automated data analytics ensures that businesses can receive real-time, efficient insights from the collected data. While humans can take months to arrive at a conclusive decision, automated applications can make hundreds of decisions in just a few seconds. Purposeful decisions taken with the help of these insights lead to rewarding results.

  3. Improved productivity
  4. Data analysts spend a considerable amount of time managing data life cycle assignments. This includes performing mundane tasks like data clean-up, organisation, or data visualisation. With automated data analytics, people get back their time so they can take care of higher-value tasks. Automation not only simplifies data management but also guarantees a reduction in manual errors. The complexity of observing vastly changing data is reduced, and analysts can easily focus on detecting tiny anomalies or discovering hidden patterns to arrive at hugely beneficial decisions.

  5. Cost optimisation
  6. Enterprises spend a significant amount of money on data preparation, modelling, and analytics. By incorporating data analytics automation, organisations can automate the entire data life cycle, including data collection, data fostering, data clean-up, data analytics, data modelling, and reporting. The amount saved by avoiding manual efforts can be reinvested to scale up automation efforts.

  7. Avoiding human biases
  8. When large volumes of data are available, it becomes imperative for organisations to follow a data-driven decision-making approach. However, the person using this data to arrive at a decision is always bound by desire, emotions, and knowledge. By automating the decision-making process with data, we eliminate any human bias that could impact the outcome by challenging the underlying assumptions.

    While implementing AI-based data analytics automation, the biggest challenge is to find people with data science and coding skills. Although the benefit of adopting automation is significant, overcoming the hurdle of finding the required skills can be quite daunting. As automated data analytics moves to the next level, the solutions have also become smarter and more convenient to implement. There are many data analytics automation solutions available that can be used without coding skills. These work on no-code workflow models, thereby reducing the requirement for niche technical skills. AI-enabled automated data analytics is transforming the future of every business by bringing agility*. The future of data analytics automation is only going to be rich as long as we mitigate its negative effects.

    *For organizations on the digital transformation journey, agility is key in responding to a rapidly changing technology and business landscape. Now more than ever, it is crucial to deliver and exceed on organizational expectations with a robust digital mindset backed by innovation. Enabling businesses to sense, learn, respond, and evolve like a living organism, will be imperative for business excellence going forward. A comprehensive, yet modular suite of services is doing exactly that. Equipping organizations with intuitive decision-making automatically at scale, actionable insights based on real-time solutions, anytime/anywhere experience, and in-depth data visibility across functions leading to hyper-productivity, Live Enterprise is building connected organizations that are innovating collaboratively for the future.

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