Articles & Books From Big Data

Article / Updated 12-01-2023
Getting the most out of your unstructured data is an essential task for any organization these days, especially when considering the disparate storage systems, applications, and user locations. So, it’s not an accident that data orchestration is the term that brings everything together.Bringing all your data together shares similarities with conducting an orchestra.
Cheat Sheet / Updated 04-12-2022
Big data makes big headlines, but it’s much more than just a buzz phrase or the latest business fad. The phenomenon is very real and it’s producing concrete benefits in so many different areas – particularly in business. Here you will get to the heart of big data as a business owner or manager: You will take a look at the key terminology you need to understand the crucial big data skills for businesses, ten steps to using big data to make better decisions, and tips for communicating insights from data to your colleagues.
Cheat Sheet / Updated 03-10-2022
Summary statistical measures represent the key properties of a sample or population as a single numerical value. This has the advantage of providing important information in a very compact form. It also simplifies comparing multiple samples or populations. Summary statistical measures can be divided into three types: measures of central tendency, measures of central dispersion, and measures of association.
Cheat Sheet / Updated 02-09-2022
To stay competitive today, companies must find practical ways to deal with big data — that is, to learn new ways to capture and analyze growing amounts of information about customers, products, and services.Data is becoming increasingly complex in structured and unstructured ways. New sources of data come from machines, such as sensors; social business sites; and website interaction, such as click-stream data.
Article / Updated 03-26-2016
The technical jargon surrounding big data can seem a little daunting at first. The key phrases and terms you’re likely to come across, with easy-to-understand definitions for each, follow: Big data: Increasingly, everything you do leaves a digital trace (or data), which you (and others) can use and analyse. The phrase big data refers to that data being collected and the ability to make use of it.
Article / Updated 03-26-2016
Cloud computing is a method of providing a set of shared computing resources and is becoming increasingly important for your big data initiative. The cloud includes applications, computing, storage, networking, development, and deployment platforms, as well as business processes. Cloud computing turns traditional siloed computing assets into shared pools of resources based on an underlying Internet foundation.
Article / Updated 03-26-2016
A histogram is a graph that represents the probability distribution of a dataset. A histogram has a series of vertical bars where each bar represents a single value or a range of values for a variable. The heights of the bars indicate the frequencies or probabilities for the different values or ranges of values.
Article / Updated 03-26-2016
While the worlds of big data and the traditional data warehouse will intersect, they are unlikely to merge anytime soon. Think of a data warehouse as a system of record for business intelligence, much like a customer relationship management (CRM) or accounting system. These systems are highly structured and optimized for specific purposes.
Article / Updated 03-26-2016
Many companies are exploring big data problems and coming up with some innovative solutions. Now is the time to pay attention to some best practices, or basic principles, that will serve you well as you begin your big data journey. In reality, big data integration fits into the overall process of integration of data across your company.
Article / Updated 03-26-2016
Big data is most useful if you can do something with it, but how do you analyze it? Companies like Amazon and Google are masters at analyzing big data. And they use the resulting knowledge to gain a competitive advantage. Just think about Amazon's recommendation engine. The company takes all your buying history together with what it knows about you, your buying patterns, and the buying patterns of people like you to come up with some pretty good suggestions.