White Paper: Fusionex International
Making data-driven decision in a complex big data environment presents many challenges for organizations . What is driving organizations to rethink new approaches to shorten the path to data-driven decisions making??
This whitepaper highlights the top priorities as well as challenges that hinders wider adoption of data-driven decision making. It addresses questions like:
What challenges organizations are facing in making data -driven-decisions ?
What are the key offerings that address the organizations' needs in this process of driving decisions from data?
What are the considerations CXOs need to take into account when implementing infrastructure and tools to support the data-driven decision making path?
What are the benefits of leading with data-driven decisions in solving business problems?
This informative whitepaper comprehensively explains the key trends impacting big data and analytics including:
Digitization of Everything: Managing and analyzing new sources of data effectively
Security and compliance regulations in the process of driving decisions from data
New expectations for information access in making decisions based on data
Four undeniable trends shape the way we think about data – big or small. While managing big data is ripe with challenges, it continues to represent more than $15 trillion in untapped value. New analytics and next-generation platforms hold the key to unlocking that value. Understanding these four trends brings light to the current shift taking place from Big Data 1.0 to 2.0, a cataclysmal shift for those who fail to see the shift and take action, a catalyst for those who embrace the new opportunity. Key take aways from this white paper: 5 Advancements of Big Data 1.0 5 Challenges of Big Data 1.0 Big Data 2.0 – Transformational Value Big Data 2.0 Means Big Value Times Ten
By: Fusionex International
Big data analytics and the Internet of Things in manufacturing Industry as an end-to-end platform is the critical backbone to enable the vision of smart manufacturing. Smart manufacturing requires IoT-driven data analytics to improve asset utilization and greater efficiency.The application of the Internet of Things to the manufacturing sector signifies huge operational improvements. This whitepaper outlines an Internet of Things (IoT) initiative in manufacturing to show how data analytics applied to factory equipment and sensors can bring operational efficiency. Is the Internet of Things really changing Manufacturing? How Big data analytics in manufacturing can bring cost savings to manufacturing processes? What are the key benefits of manufacturing optimization with the Internet of Things? How to apply IoT in the manufacturing industry's unique requirements? How can Iot help manufacturers to extract maximum value out of their manufacturing data? How can an IoT initiative using big data analytics server and IoT gateway in manufacturing address the challenges? Read this whitepaper to know more about How to Optimize Manufacturing smartly with the Internet of Things (IoT).
What is Big Data ?
Big data is the act of collecting huge amount of enterprise data that can be used for future analysis. Big data helps all kind of industry data to grow securely that includes government, banking, retail, education and healthcare. Big data stores all kind of data including structured, unstructured and semi structured data, which contains valuable information about core functions of an enterprise such as finance, marketing, procurement.
What is Data Management ?
Data management is the development and execution of policies and procedures in order to manage the information lifecycle needs of an enterprise ensuring the accessibility, reliability, and timeliness of the data for its users. Data Management enables organizations and enterprises to use data in: Organizing the enterprise data, Storing and preserving data for future re-use, Making data ready to use anytime, Share data with colleagues
What is Big Data analytics ?
Big Data analytics involves the assembling, arrangement, and analyzes of enormous data sets with varying contents, to reveal or establish existing trends, relations, or patterns. Big data analytics requires tools for data mining, forecasting, optimization, and analysis. Enterprises involved in big data analytics receive insights not only on their companies functionalities but also on customer preferences and interactions