Semi-Structured Data

The data, not represented in the traditional manner with the application of regular methods is known as semi-structured data. This data is neither totally structured nor unstructured but contains some tags, data tables, and structural elements. Few examples of semi-structured data are XML documents, emails, tables, and graphs.

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36 percent of investment professionals use web scraping to derive data.
Content analytics usage among IT professionals increased from 43 percent to 54 percent between January 2018 and January 2019.
59 percent of executives say big data at their company would be improved through artificial intelligence (AI).
Businesses that use big data saw a 10 percent reduction in overall cost.
79 percent of enterprise executives say that not embracing big data will cause companies to lose competitive position and risk extinction.
61 percent of businesses that recognize the effect of data and analytics on their core business practices say their companies either have not responded to these changes or have taken only ad hoc actions rather than developing a comprehensive, long-term strategy for analytics.
By 2025, IDC predicts that the total amount of digital data created worldwide will rise to 163 zettabytes, ballooned by the growing number of devices and sensors
98 percent of sales representatives at construction companies that adopt analytics and geographic data reported dramatic decreases in their time frame for providing price quotes.
62 percent of retail businesses see competitive advantages from information and analytics.
Insights-driven businesses are growing at an average of more than 30% each year, and by 2021, they are predicted to take $1.8 trillion annually from their less-informed peers.

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