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Posts Tagged ‘Big Data’

Why Businesses Shouldn’t Miss Out On Big Data and AI

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“The world’s most valuable resource is no longer oil, but data.” 

That statement from The Economist in 2017 cannot be overstated. Businesses in all shapes and sizes must realize that adapting to an already data-driven world is the only way to survive, connect, and thrive.

Artificial Intelligence (AI) was introduced in the 1950s by a computer researcher named John McCarthy. He defined AI as “the science and engineering of making intelligent machines.”

Nowadays, innovation pioneers like Microsoft, Google, and IBM have made strides in AI advancement to back cloud analytics, client engagement, and more. AI has become a program outlined to complete tasks that would regularly require human capabilities or input. AI is considered an innovation that takes after or mirrors human insights and actions, including speech, reviewing pictures, or making a conversation. To a great extent, AI can do those things by recognizing designs inside the information and reacting based on pre-defined rationale.

On the other hand, big data is an extensive, fast, and diverse information resource that requires advanced forms of processing to improve decision making, knowledge generation, and process optimization. 

Big data describes  sets of information created in different formats and through different sources, such as software applications, IoT sensors, customer feedback surveys, videos, and images.. 

Big datasets are developed by collecting large amounts of information from real-time data streams, established databases, or legacy datasets. As the environment constantly changes and grows, we need powerful software to protect, classify, and explain information for both short-term and long-term use. 

Organizations often use a combination of cloud-based applications and data warehousing tools to develop analytic architectures that collect, organize, and visualize data. AI-powered tools are central to tailoring many of these moving parts to consistent insights that support decision-making.

Linking Up Big Data and AI for Business

Implementing big data with AI has already been vital for many businesses that aim to have a competitive edge. It doesn’t really matter whether it is a new company or an established leader in the market. They use data-driven strategies to turn information into perceptible value. It is common to find big data in almost every industry, from IT and banking to agriculture and healthcare.

Business experts acknowledge that big data and AI can create new ideas for growth and expansion. There is even a possibility that a new type of business will become popular soon: data analysis and aggregation companies for particular industries. The purpose of those organizations is to process enormous flows of data and generate insights. Before this happens, businesses should empower their big data capabilities intensively. In the past, estimations were made based on the retroactive point of view. Leveraging real-time analysis, big data can empower predictions and allow strategists to test assumptions and theories faster.

Data and AI are typically applied to analytics and automation, helping businesses transform their operations in the process.

Analytics tools like Microsoft, Azure, and Synapse help organizations predict or identify trends that inform decision-making around product development, service delivery, workflows, and more. Additionally, your data will be organized into dashboard visualizations, reports, charts, and graphs for readability.

Big data and AI in Health

The global market for AI-driven health care is expected to register a CAGR of 40 percent through 2021 and to up from USD 600 million in 2014. Further advances in AI and big data provide developing countries with opportunities to solve existing challenges in the health care access of their populations. AI combined with robotics and IoMT could also help developing countries address healthcare problems and meet SDG 3 on good health and well-being. AI can be deployed in health training, keeping well, early disease detection, diagnosis, decision-making, treatment, end-of-life care, and health research. For instance, AI can outperform radiologists in cancer screening, particularly in patients with lung cancer. Results suggest that the use of AI can cut false positives by 11 percent.

Big data and AI in Agriculture

Today’s global population of 7.6 billion is expected to rise to 9.8 billion by 2050, with half of the world’s population growth concentrated in nine countries, such as India, Nigeria, the Democratic Republic of the Congo, Pakistan, Ethiopia, the United Republic of Tanzania, the United States of America, Uganda, and Indonesia. 

The growing demand for food will put massive pressure on the use of water and soil. All of this will be exacerbated by climate change and global warming. 

Big data and AI in Education

AI can reshape high-quality education and learning through precisely targeted and individually customized human capital investments. Incorporating AI into online courses enhances access to affordable education and improves learning and employment in emerging markets. Also, AI technologies can ensure equitable and inclusive access to education, providing marginalized people and communities, such as persons with disabilities, refugees, and those out of school or living in isolated communities, with access to appropriate learning opportunities.

Expected Economic Gains from AI Worldwide

AI could contribute up to USD 15.7 trillion to the global economy in 2030, more than the current GDP of China and India combined. Of this, USD 6.6 trillion will be derived from increased productivity and USD 9.1 trillion from the knock-on effects of consumption. The total projected impact for Africa and Asia-Pacific markets would be USD 1.2 trillion. For comparison, the combined 2019 GDP for all countries in sub-Saharan Africa was USD 1.8 trillion. Thus, the successful deployment of AI and big data would open up a world of opportunities for developing countries.

The big data market is expected to grow tremendously over the projected years. One of the important reasons is the rapid increase in the amount of structured and unstructured data. Factors include the increasing penetration of technology and the proliferation of smartphones in all areas of life. This leads to a large amount of data. 

Other industries such as healthcare, utilities, and banking make extensive use of online platforms to provide enhanced services to their customers. 

Intelligent use of big data in day-to-day operations enables you to make data-driven decisions and respond quickly to market trends that have a direct impact on business performance.

If you would like to learn more about the best practices for analyzing data, sign up for The KPI Institute’s Data Analysis Certification.

Big Data: The Next Frontier of Performance Management

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Image Source: Tumiso | PIxabay

The value of Big Data has found its way to the core of many organizations. NewVantage Partners’ 2021 executive survey showed that 99.0% of the companies they surveyed are investing in data initiatives while 96.0% attest that Big Data and AI efforts were generating results. 

However, working with Big Data is not easy for all companies. The survey revealed that 92.2% of leading companies consider culture (people, process, organization, and change management) as the top reason why becoming a data-driven organization remains challenging.  

Organizations should recognize that integrating Big Data into performance management would allow them to further improve their performance , make strategic decisions, and achieve higher efficiency in many areas of business. 

How does that happen? First, it is important to know what Big Data is and what it is not. 

Big Data is not about having a higher volume of data. IBM defines Big Data as “a way of harvesting raw data from multiple, disparate data sources, storing the data for use by analytics programs, and using the raw data to derive value (meaning) from the data in a whole new way.”

Mayer-Schönberger and Cukier, authors of “Big Data: A Revolution That Will Transform How We Live, Work, and Think,” wrote that Big Data can generate new insights and develop new forms of value in a manner that changes how people live.  

The reason is that Big Data can reveal trends and patterns. In an ever-changing business landscape, organizations working with Big Data would allow them to make decisions based on facts. This echoes what Geoffrey Moore, a famous American organizational theorist & author of “Crossing the Chasm,” was quoted saying: “Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway.”

Big Data’s Role in Performance Management and Measurement

The value of Big Data lies in improving the performance and processes of an organization. 

For instance, Big Data can provide insights into customer preferences. Understanding customer preferences and using them as a basis for strategies can lead to increased sales. With better forecasting, Big Data can guide companies in determining where they need to invest. A manufacturing company would be able to accurately identify the equipment that needs replacing. Moreover, the automation of high-level business processes can make organizations more effective and efficient. 

In the conference paper, “Is Big Data the Next Big Thing in Performance Measurement Systems?” the authors concluded that the presence of a variety of data could expand the horizons of PMSs due to the application of different kinds of metrics. The applications of Big Data in PMS are in planning, controlling, and improving business performance as well as in strategic planning, controlling operations, and processes improvement.

The authors found the reasons for using Big Data and PMSs similar, and they revolve around decision-making and action-taking. “PMS supports decision-making [by] providing meaningful and appropriate data [developed] through a series of activities, such as analyzing and interpreting data from past actions to influence the future performance.”

Big Data in Action

The success of Netflix,  a streaming service company, is attributed to their usage of Big Data. For content development, their objective is to determine what their audience would want to watch next. To analyze the behavior and preferences of their over 140 million subscribers, Netflix used metrics, such as “What day you watch content,” “Searches on the platform,” “User location data,” “When you leave content,” “The ratings given by the users,” and even “Browsing and scrolling behavior.”

Netflix also uses Big Data in addressing challenges in production planning, such as determining shoot locations and arranging a shoot schedule. With prediction models, Netflix can minimize their efforts and reduce their expenses.

Xerox, the world’s largest provider of digital document solutions, once faced a problem with its workforce and needed to cut employee training costs and lower the premature attrition of its employee pool. With the help of Big Data, the company executed a predictive recruiting program in order to assess and filter applicants. Big Data and Big Data analytics helped them recruit people who have more technical skills and are more likely to stay longer with them. This means lower cost of training. The reduced attrition successfully helped the enhancement of Xerox’s bottom line.

Big data is a new source of competitive edge for any organization as it permits them to provide faster and more intelligent decisions, makes information more transparent, generates unprecedented insights into market situations and customer behavior, and optimizes business performance.

If you would like to discover new knowledge and the practical application of best practices used in analyzing statistical data, sign up for The KPI Institute’s Data Analysis Certification.

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