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  1. How Data Is Driving Big Organizations and What to Learn From It

    How Data Is Driving Big Organizations and What to Learn From It

    Categories: Data Science
    Well-managed and reliable data leads to reliable analyzes and reliable decisions. To stay competitive, companies need to take full advantage of big data and act on data - making big data decisions, not intuition. The benefits of using data-based are obvious. Data organizations operate better, more predictably, and more efficiently. It is collected quickly and in large quantities to identify trends and patterns that drive customers, industry, and life itself.
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  2. Machine Learning Cheat Sheet

    Machine Learning Cheat Sheet

    Categories: Data Science , Cheat Sheet
    Machine learning is the method of algorithms understanding processes without programming. As part of artificial intelligence (AI), machine learning accesses data and learns by itself. It’s a fascinating field of study that can even be used to predict future events based on past data. Predictive analytics, deep learning, algorithms, and supervised and unsupervised learning are all part of machine learning. Many advancements in AI are due to machine learning algorithms. This could range from recommendations you see on YouTube, Google and other major sites that track data, such as clicks, likes and frequented websites. In this way, the algorithm “learns” what you like and provides recommendations.
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  3. What Is Data Governance? A Best Practices Framework for Managing Data Assets

    What Is Data Governance? A Best Practices Framework for Managing Data Assets

    Categories: Data Science
    In this era, you can learn a lot from other people who have worked on different processes and models by researching best practices in data - governance. However, every single business is varying from another and one has to adopt the customs of data - governance customs to the process. Though, it is not required to wholly build the wheel. Use agile evolutionary thinking in data governance, start with the least efficiency, then repeat and expand from there. For most companies, data is often collected for action purposes.
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  4. What Is A Data Architect? It’s a Data Framework Visionary

    What Is a Data Architect? It's a Data Framework Visionary

    Categories: Data Science
    In this interconnected world, it is believed that data - architects are the ones who are known as experienced visionaries - that can interpret the demands of the industry into a practical condition. On the other hand, also outline data principles as well as standards for the industry. The data architect also provides a standard unified terminology, sets strategic requirements, describes a high-level integrated design to meet those requirements, and is consistent with company policies and related business architectures. All the same, the data - architect framework describes the processes used to organize, identify, activate, create, manage, distribute, monitor, and clean data.
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  5. Data Gravity and What It Means For Enterprise Data Analytics and AI Architectures

    Data Gravity and What it Means for Enterprise Data Analytics and AI Architectures

    Categories: Data Science
    In this era, all of us are thriving in the age of data. All the same, the new age data-intensive tools such as Artificial - Intelligence (AI), Machine - Learning (ML), Data Analytics along with the Internet - of - Things (I-o-T) turn out to be the main choice of apps, and companies are financing them. This turnover has led to the requirement to influence this data, driving companies to develop the newest set of Information Technology design with the help of Data analysis training. However, it is revolving nearby the idea of data gravity. Data gravity seems to be the concept reliant on the universal gravitation law of Newton, to define the phenomenon on behalf of the digit and the quickness where services, apps, and even consumers are attracted towards data.
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  6. What Are Data Centers? How They Work and How They Are Changing

    What Are Data Centers? How They Work and How They Are Changing

    Categories: Data Science
    With time, it is believed that the future of data centers is bright. In the United States alone, the data center market is expected to reach $ 15 billion by 2023, and the global data center market will reach $ 180 billion in the coming times. However, the driving force behind this growth is the continued adoption of the Internet of Things and other advanced technologies - such as Cloud computing, big data analysis, and Artificial Intelligence (AI), which alone can generate billions of dollars in Gross - Domestic - Product (G-D-P) in the next decade.
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  7. Is Data the Currency of 2021

    Is Data the Currency of 2021

    Categories: Data Science
    We live in a digital world, a century in which all companies are witnessing strong development. A new powerful form of currency has a radical definition of human business: DATA. The scope and frequency of Internet use have generated a lot of data, and companies have created various business models around this resource in the 21st century. The value of personal data will soon be open to the average user, but researchers and companies will also have better access.
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  8. Data Science Cheat Sheet

    Data Science Cheat Sheet - 2021 Edition

    Categories: Data Science , Cheat Sheet
    The data science field involves many different disciplines and languages which makes it difficult to write a cheat sheet involving most of them. A few come to mind: popular programming languages like Python, SQL and R. Our courses go into great detail about these languages and much more. to gain access to over 80 free courses.
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