Data types involved in Big Data analytics are many: structured, unstructured, geographic, real-time media, natural language, time series, event, network and linked. It is necessary here to distinguish between human-generated data and device-generated data since human data is often less trustworthy, noisy and unclean.
A brief description of each type is given below.
Types of data used in big data analytics
- Structured data: data stored in rows and columns, mostly numerical, where the meaning of each data item is defined. This type of data constitutes about 10% of the today’s total data and is accessible through database management systems.
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Businesses have recognized the benefit rooted in data and, therefore, put together people, technologies, and processes to collect, store and analyze huge amounts of data. A key element for deriving value from data is by using analytics.
Big Data analytics is a business strategy that uses technology to gain deeper insights into customers, partners and businesses and so achieving competitive advantage. It includes working with huge data that, because of its size and variety, lie beyond the ability of typical database management systems to store, manage and analyze.
The use of “Big Data analytics” involves two dimensions: one is Big Data, which is annotated with the three ‘Vs’: data volume, velocity, and variety.… Click to read the full post
Data analytics, as defined in “Competing on Analytics: The New Science of Winning” by Thomas H. Davenport and Jeanne G. Harris, refers to the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to derive decisions and actions. It has the meaning of discovery and communication of meaningful patterns in data.
Dealing with business analytics implies the efficient use of quantitative analysis, statistics, as well as information modelling to shape business decisions. In this context, people dealing with business analytics can be classified into three levels: analytics scientists who build complex models to extract insights from data, analytics experts who apply the models from the first level to real business problems, and analytics specialists who can build insights based on the output of the previous steps.… Click to read the full post
It was almost a year ago when I challenged Agro-Know’ers to do something that was considered unthinkable and unspeakable: to Hire The Boss to do their dirty jobs. Despite my mythical blog post on this, people still look at me in a strange way and laugh when I knock on their doors to get hired. Although about 10 people have already hired me for about half a day to do something for them that completely tires or bores them, it still seems that there are team members that are not really convinced that I can deliver some serious work if they hire me. … Click to read the full post