The Impact of Machine Learning in a Data-Driven Economy

The Impact of Machine Learning in a Data-Driven Economy

Businesses gather a ton of information – and with machine learning, there’s finally a way to use it.

With the right tools, businesses can now analyze and find meaning in their data, quickly and reactively improving decision-making. Drawing meaning from data means consumers will have access to better products and services, and businesses will be able to create better targeting strategies.

The World of Data Will Grow Fifty-Fold Between 2018 and 2025

The volume of data generated worldwide will continue to increase:

  • By 2020, humans will generate 1.7 megabytes of new information per second.
  • By 2020, the accumulated volume of big data will increase from 4.4 zettabytes to roughly 44 zettabytes – or 44 trillion GB.
  • In just 5 years, the number of smart devices in the world will be more than 50 billion – all of which will create data that can be shared, collected and analyzed.

More and more data will be generated from connected devices, mobile phones, wearables, and sensors. As a result, it will become necessary to develop a “data culture” in the business sector, where every organization understands the importance of adopting a data management strategy, including new types of data and analysis techniques.

Organizations capable of analyzing and exploiting information with a business vision will stand out from the rest, saving time and money while delivering the right products to their customers.

Data Is the New Water and Machine Learning Is the New Electricity

For businesses, data-driven decisions will make the difference between succeeding and falling further behind. Machine learning will play a big part in the future of big data, helping businesses to prepare data and conduct predictive analyses so that they can face future challenges easily.

It is practically impossible to think of the efficient use of big data without thinking of Machine Learning technology. Some companies use large amounts of data that cannot be analyzed by humans alone. Companies like Amazon use Machine Learning algorithms to improve their services.

While many organizations are still not ready to implement Machine Learning because their data is in a poor, unreliable state, Machine Learning technology can be used to help improve data quality first. Machine Learning can be the key to unlocking the value of big data, improving strategic decision-making as well as productivity and cost savings.

The combination of Machine Learning and Big Data is invading mass consumption markets and moving to smaller companies to ensure their survival. Gathering data in real-time, reducing risks or simplifying operations are some of the reasons businesses across all industries choose to improve operations using this technology.

Businesses can utilise the power of Machine Learning and Big Data to drive their business forward. Building custom software as an Intelligent Product using ML techniques can help businesses to achieve specific goals, overcome challenges, and expand their overall capabilities.

Read our blog post to learn how to launch your custom software project successfully.

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