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5 Key Challenges In Today's Era of Big Data

#artificialintelligence

Digital transformation will create trillions of dollars of value. While estimates vary, the World Economic Forum in 2016 estimated an increase in $100 trillion in global business and social value by 2030. Due to AI, PwC has estimated an increase of $15.7 trillion and McKinsey has estimated an increase of $13 trillion in annual global GDP by 2030. We are currently in the middle of an AI renaissance, driven by big data and breakthroughs in machine learning and deep learning. These breakthroughs offer opportunities and challenges to companies depending on the speed at which they adapt to these changes.


5 Key Challenges In Today's Era of Big Data

#artificialintelligence

Digital transformation will create trillions of dollars of value. While estimates vary, the World Economic Forum in 2016 estimated an increase in $100 trillion in global business and social value by 2030. Due to AI, PwC has estimated an increase of $15.7 trillion and McKinsey has estimated an increase of $13 trillion in annual global GDP by 2030. We are currently in the middle of an AI renaissance, driven by big data and breakthroughs in machine learning and deep learning. These breakthroughs offer opportunities and challenges to companies depending on the speed at which they adapt to these changes.


Top 5 Scary Things About Big Data

#artificialintelligence

Today we will be learning some key concepts of Big Data and some of the major challenges a company faces while dealing with Big Data.Before discussing on harder topics lets first begin with "What is Big Data? Big data as its name suggests dealing with huge volume of data.There is no set number of gigabytes or terabytes or petabytes that separates "big data" from "average-sized data." Data stores are constantly growing, so what seems like a lot of data right now may seem like a perfectly normal amount in a year or two. Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many cases (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. As mentioned above dealing with Big Data sometimes becomes cumbersome and devastating to handle.


Fostering Big Data Challenges with AI Applications

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Big data is the confidential information storage of a company. Like how a flight's black box contains everything that happens in the journey, big data collects all the information about an organisation and stores it together. Big data describes the high volume of data that are both structured and unstructured which inundates a business on a day-to-day basis. The big data storage is spread across various computers as a single system can't manage such huge data. Big data is considered as a credible and useful source because it can be analysed with AI applications.


System of Intelligence: Building an IoT Learning Loop

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Why is your organization building a connected system? Whatever particular story fits your business, industrial investment in IoT is about value creation. It's about collecting data from environments and assets, and transforming raw machine signals and external events into information used to improve performance. These outcomes are made possible when you know the state of your machines and the world around you at each moment in time. These are the outputs of the new Systems of Intelligence created by data-focused, flexible, secure, and scalable IoT solutions.