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Machine learning is the key technology to the future of business. AI-driven software has already helped companies improve efficiency, customer relations, and increase sales. Researchers estimate that machine learning has the potential to add $2.6 trillion in value to the marketing and sales industry by 2020, as well as another $2 trillion to manufacturing and logistics fields. According to the International Data Corporation, machine learning spending will amount to $77.6 Billion by 2022. Companies of all sizes collaborate with Python development outsourcing companies to source data scientists and create custom data analytics software.

Because of the availability of various data analytics software, it is possible to examine the large quantity of data utilized for competitive benefits. This software is used for mining the data, which helps to track a various array of business activities. These activities involve current sales data and historic inventories information that can be processed based on scientific queries. Several linked technologies enable visualization software to represent the outcomes of the data. These involve ETL tools, data warehouse devices, and sometimes cloud computing support too.

Data analytics is nothing new and neither is Artificial Intelligence (AI). Over the next few years, the impact of data analytics on the world will ramp up remarkably. In fact, the global market for data analytics is expected to be valued at over USD 77.64 billion, expanding at a CAGR of 30.08% by 2023. This is primarily because of the increased data generation and the ability to use statistical algorithms and the latest machine learning approaches to deliver actionable insights. Data analytics can be used at a business scale to drive revenue, provide solutions to emerging trends, optimize marketing, and improve overall efficiency to create a competitive advantage.

Can your data talk intelligently? AI plugged into data management systems aims to do just that! Intelligent analytics offers a classic approach to discover the hidden intelligence behind historical and real-time data. This myriad suite of analytical techniques and algorithms can parse mind-boggling amounts of data generated in real-time to discover the hidden gems that are often missed or go undetected by traditional statistical methods. The methodology of mixing intelligence with analytics reaches far beyond.

Every technology revolution has a unique inflection point. The spark that ignited the artificial intelligence movement was a statistical data analysis system developed by Jim Goodnight when he was a statistics professor at North Carolina State University 45 years ago. He never imagined that the technology he created to improve crop yields would evolve into sophisticated data analytics software, a precursor to modern day AI. Back then computers could only compute 300 instructions a second and had 8K of memory. Today they can execute 3 billion instructions a second and contain multiple terabytes of memory.

Machine learning is the most important technology for the business of the future. That's because AI-driven software is already helping companies increase efficiency, improve customer relationships, and boost sales. Researchers estimate that machine learning has the potential to add $2.6 trillion in value to the marketing and sales industry by 2020, as well as another $2 trillion to manufacturing and logistics fields. The International Data Corporation estimates that spending on machine learning will reach $77.6 billion by 2022. This is why companies of all sizes are collaborating with Python development outsourcing firms to source experienced data scientists as needed and develop custom data analytics software.

Machine learning is the most important technology for the business of the future. That's because AI-driven software is already helping companies increase efficiency, improve customer relationships, and boost sales. Researchers estimate that machine learning has the potential to add $2.6 trillion in value to the marketing and sales industry by 2020, as well as another $2 trillion to manufacturing and logistics fields. The International Data Corporation estimates that spending on machine learning will reach $77.6 billion by 2022. This is why companies of all sizes are collaborating with Python development outsourcing firms to source experienced data scientists as-needed and develop custom data analytics software.