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Cisco predicts that annual global IP traffic will reach 3.3 ZB per year by 2021 and that the number of devices connected to IP networks will be more than three times the global population by 2021, while Gartner predicts $2.5M per minute in IoT spending and 1M new IoT devices will be sold every hour by 2021. It’s testament to the speed with which digital connectivity is changing the lives of people all over the world.
Data has also evolved dramatically in recent years, in type, volume, and velocity -- with its rapid evolution attributed to the widespread digitization of business processes globally. Data has become the new business currency and its further rapid increase will be key to the transformation and growth of enterprises globally, and the advancement of employees, "the digital natives."
The Cisco Global Cloud Index points to the cloud as the top driver as exponential data center growth with cloud center traffic quadrupling in the next five years. Data generated by IoT applications (such as connected homes, smart cities and healthcare) will be 600ZB (zettabytes) per year by 2020, 39 times higher than current data center traffic which is 15.3ZB.
Big data therefore has a far-reaching impact and meaning. But how do we understand it and its benefits, along with analytics on the journey to digital transformation? Understanding the value of data is key to the successful implementation of operational strategies that facilitate agile and effective business growth.
Big data means better business
Data is an enabler of future strategies and immediate change, thanks to the power of predictive analytics and advanced data science. Correctly harnessing data can help to achieve better, fact-based decision-making and improve the overall customer experience. By using new big data technologies, organizations can answer questions in seconds rather than days, and in days rather than months. This acceleration allows businesses to enable the type of quick reactions to key business questions and challenges that can build competitive advantage and improve performance, and provide answers for complex problems or questions that have resisted analysis...
Keep learning -- skills are everything
Proficiency with data mining and visualization tools ranks as one of the most important skills in determining project success.
All organizations need to consistently develop new data mining skills to fully realize the business potential. A key trend in big data is machine learning. Big data experts who can harness machine learning technology to build and train predictive analytic apps such as classification, recommendation, and personalization systems are in high demand.
Statistical and quantitative analysis, which aims to understand or predict behavior or events through the use of mathematical measurements and calculations, statistical modeling and research, is also imperative to accomplishment. Other key data mining techniques that are employed industry wide include:
- Association is one of the best-known data mining techniques. With association, a pattern is discovered based on a relationship between items in the same transaction
- Classification is a classic data mining technique based on machine learning
- Clustering is a data mining technique that makes a meaningful or useful cluster of objects which have similar characteristics using the automatic technique
- Prediction is one of a data mining techniques that discovers the relationship between independent variables and relationship between dependent and independent variables
- Sequential patterns analysis seeks to discover or identify similar patterns, regular events or trends in transaction data over a business period
- Decision tree technique, the root of the decision tree is a simple question or condition that has multiple answers
Source: BetaNews
