Successful data management in the age of big data is a challenge. Applying data quality best practices while making adjustments and optimizations can help your organization meet its business goals. In this course, you'll learn about using data science in data quality management. You'll learn how to determine the quality of data, challenges and solutions for gathering quality data, and how to assess the value of data.

Data science involves using scientific analysis, tools, and mathematics to extract useful insight from raw data, and then applying that knowledge for effective business strategy. Increasingly, companies are turning to data science. They can use scientific analysis, tools, and mathematics to extract useful insight from Big Data, to guide their decisions and drive business improvements. In this course, you'll learn about the characteristics and key elements of data science, and its potential benefits for organizations. You'll also learn what skill sets are required on a data management team, best practices for extracting useful, actionable insights from data, and common challenges organizations face in using data science.

Professional marketers today have unprecedented access to customer data and complex data sets. By using Big Data technologies and analytical tools, they can gather insights about their target markets through things like website traffic, e-mail marketing, and social media activity. And they can glean incredibly useful information from dealing with Big Data to help drive effective operational marketing strategy. In this course, you'll learn about the characteristics of Big Data, the benefits of managing Big Data for marketing purposes, the key challenges associated with using Big Data, and the best practices for data storage and handling methods. The course also covers considerations when implementing Big Data strategies.

Modeling data can help businesses better organize and access data. Organizations rely on various kinds of data, including Big Data, to fully understand their business. To do so, they need that data to be easy to access and understand. Data modeling plays a critical role in both of these. In this course, you'll learn about the characteristics of data modeling, and the common styles and types of data models used. You'll find out how the three levels of data modeling can provide a detailed blueprint of a company's data. And you'll also learn about common strategies for building data models, and how doing so improves an organization's daily operations.

Using social intelligence (SI) is not just about recording the number of likes, retweets, or followers you have on your various social media outlets. True social intelligence involves using the vast amount of raw, real-time data you have at your disposal and converting it into practicable insights to improve customer relationships. In this course, you'll learn about the benefits of social intelligence to your organization's performance. You'll explore how to monitor social media, as well as common sources of social media data. Finally, you'll discover best practices for analyzing that data, common mistakes to avoid, and ways to use social-awareness strategies that deliver real business value.