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The Growing Importance Of Data Collection For Customer Service

Smart Data Collective

Big data is crucial for any organization that wants to attract and retain customers. A study by McKinsey Global Institute found that data-driven companies are 400% more likely to retain customers and 2,200% more likely to acquire new ones. Freshdesk published an article on the importance of big data in customer service.

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A history of tech adaptation for today’s changing business needs

CIO Business Intelligence

The first was becoming one of the first research companies to move its panels and surveys online, reducing costs and increasing the speed and scope of data collection. The initiative follows agile methodologies to offer faster and better results to its clients.

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Q&A: Leading IT in a high-volume M&A environment

CIO Business Intelligence

AssuredPartners is a full-service insurance broker providing commercial insurance, risk management, and employee benefits. Martha Heller: AssuredPartners was founded in 2011 and just crossed the $2 billion revenue mark. How is data collected and used in the organization? What is behind that growth?

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Analytics and BI Bake-Off Rocks Data & Analytics Summit LIVE and IN PERSON, 2022!

Rita Sallam

Last year, we used global vaccine data , In 2020, we used population health data. In past Bake-Offs, we used loneliness and happiness data, opioid epidemic data, traffic fatalities, college costs, and homelessness. At a global level the number of people without reliable access to electricity spiked in 2011.

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Is Google BigQuery The Future Of Big Data Analytics?

Smart Data Collective

If your company revolves around the manufacturing of goods or services, for example, big data can aid you in the development of your products. This can be done through the analysis of previous product success as well as the data collected from test markets and/or social groups that may dictate what commercial offerings are best received.

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Unintentional data

The Unofficial Google Data Science Blog

Implicitly, there was a prior belief about some interesting causal mechanism or an underlying hypothesis motivating the collection of the data. As computing and storage have made data collection cheaper and easier, we now gather data without this underlying motivation.