Harnessing Disruption through Data Analytics

Companies increasingly rely on data and analytics to operate, improve, and compete, and it's critically important for business users to understand the technology categories that their organizations rely on to deliver analytics. This course covers the most common technologies in use today for delivering data and analytics, as well as the main options in technology selection and architecture. This course was developed with subject matter provided by the International Institute for Analytics. ([http://www.iianalytics.com)]www.iianalytics.com).

Understanding analytics across a variety of functions enables you to be more creative and pragmatic in applying analytics in your own function and enterprise. In this course, you'll learn about the benefits of analytics, and effective applications of analytics and big data in marketing, sales, customer service, manufacturing and supply chain, and human resources functions. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

Applying analytics to solve business problems and realize business opportunities requires a creative blend of business and technical knowledge, skill, and experience. This course covers key roles, responsibilities, and structures in analytics projects. This course also covers the key subject matter expert activities performed throughout the business analytics development process. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

Organizations increasingly rely on data and analytics to operate, improve, and compete. In today's fast-paced analytics environment, you can't grow analytics capabilities without understanding your current capabilities through an analytics maturity assessment. In this course, you'll learn about an industry standard methodology for assessing the key elements of your organization's analytics capability, and techniques for raising analytics maturity individually and collectively. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

As industries, enterprises, and jobs become more data-intensive, data literacy is critical to effectively "talk data" with business colleagues and data and analytics professionals who support you in your work. This course covers fundamental concepts in data management, data quality, data privacy and protection, and data governance. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

Enterprises increasingly rely on analytics for effective decision-making, optimization, and innovation, resulting in an increased demand for an analytically literate workforce. This course covers the benefits of building your analytics literacy, as well as techniques for doing so. This course also covers some common analytics pitfalls, and best practices for supporting effective analytics practices in your organization. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

A fundamental understanding of statistical analysis methods increases your ability to effectively communicate with data analyst professionals so you can better employ analytics associated with your work. In this course, you'll learn fundamental concepts in distribution, deviation, correlation, regression, and clustering statistical analysis methods. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

Computational thinking is a structured way to understand and solve the kind of complex problems facing most organizations today. First developed in conjunction with developing computer systems, it can be applied to many situations, both computerized and not. And it can help determine the right types of computer and human actions to apply in order to solve a problem. In this course, you'll learn the characteristics of computational thinking, including problem expression, as well as of its core techniques, such as decompositions and pattern recognition. You'll also learn how abstraction is used in logical problem solving to build algorithms that create and evaluate business solutions.

Framing opportunities for effective data-driven decision making involves documenting a specific opportunity and desired business outcome. This helps to ensure that you focus resources on the right analysis, at the right time, and with the right approach. In this course, you will learn how to frame a problem by asking the right questions. You'll also learn about identifying and testing assumptions. Finally, you'll learn how to create an effective problem statement. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

High-performing enterprises employ purpose-based data sourcing to effectively address well-framed business opportunities. In this course you'll learn how to identify, scope, and validate data for effective decision making. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

Selecting an appropriate analysis method to best address the business opportunity and solve your identified problem is critical to effective data-driven decision making. In this course, you'll learn about analytics categories, business intelligence, selecting an appropriate analytical method, and evaluating and refining your analysis. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

Organizations around the world are now realizing the many advantages of using data to overhaul their business strategies and gain a competitive edge. However, data-driven decision making doesn't mean you have to ignore your intuition or past experience. In fact, when used in combination with business acumen, building a data-driven decision-making culture can be a powerful tool for change. In this course, you'll learn about the benefits that occur when an organization makes decisions using data as the basis of their choice. You'll explore best practices for taking a balanced approach to decisions that don't rely on a single perspective. And you'll also learn how to avoid common mistakes associated with using data to inform decisions.

Algorithmic business thinking helps organizations solve business problems in a systematic way. An algorithmic mindset enables organizations to turn data into improved business outcomes. This course covers the benefits, characteristics, and best practices of algorithmic business thinking.

You've probably heard of big data technologies, but what exactly are they, and how can using big data give your organization a competitive advantage? In this course, you'll learn about dealing with big data, the benefits that big data strategies provide, and the types of data and data sets big data incorporates. You'll also be introduced to the different ways it can be applied, depending on your market sector. Finally, this course covers some fundamental security challenges of big data and some best practices for managing big data through an effective information lifecycle.

Using big data can lead to significant gains for your organization. Managing big data effectively can lead to lower operating costs, better decision making, and innovative new product development. Dealing with big data means utilizing big data technologies to identify, gather, and analyze data sets and develop big data strategies that reap benefits for your organization. In this course, you'll learn about the data analysis process. You'll be introduced to the most common basic and advanced analytics methods, including data mining. You'll also learn about some of the most common big data tools and their associated uses, and some challenges to keep in mind when undertaking big data analysis activities in your organization.

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.

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.

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.

Used correctly, A/B testing helps your organization learn what changes will best fit changing customer needs. It's the process of testing two variants to determine which performs more effectively. It's about testing the user experience. An agile mindset is needed so you can capitalize on opportunities quickly. In this course, you'll learn about the characteristics and benefits of A/B testing. You'll also learn about the key activities for creating an organizational A/B test strategy. And you'll explore considerations and best practices for using A/B testing.

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.

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.

Flexibility, agility, and the ability to efficiently change between activities are critical in today's tech-centric environment. Digital innovation has transformed the business landscape. Computer data informs our decision making and computerized processes play a major part in the jobs we do. Businesses committed to embracing digital agility are the ones that excel. In this course, you'll explore the benefits and techniques for achieving organizational digital dexterity. You'll explore how to establish a tech-centric mindset and how to digitize practices to support digital dexterity. In addition, you'll learn how to gauge organizational progress toward digital dexterity and the associated strategies to sustain it.

The right story narrative can persuade and enable company leadership to make smart, informed and intentional decisions about their business. In this course, you'll learn how to build a compelling, data-driven story that adequately answers the framed problem, and motivates action among key stakeholders. This course was developed with subject matter provided by the International Institute for Analytics. (www.iianalytics.com)

The business world is full of data. Using this data strategically presents a company with serious competitive advantages. The tricky part is making sense of the data and then communicating what it means. Data visualization (or data viz, for short) provides actionable insights out of what can be complex sets of data. In this course, you'll learn the considerations for creating data visualizations and how to relay your message using data visualization tools. You'll learn how to communicate clearly using data visualizing techniques. And you'll gain insight into how to use key design best practices to ensure your visualizations are clearly and accurately telling the story you want them to.

With the use of artificial intelligence and smart devices on the rise, business networks are strained under the heavy load of data. Edge computing seeks to move data processing, collection, and delivery closer to the end user - to the so-called edge of the network. Edge data and local processing are fast becoming standard features in modern business networks. Edge computing can reduce costs and latency issues, improve data management and data warehousing, and enhance business continuity. In this course, you'll learn about the benefits and challenges of edge computing. You'll also learn how to properly utilize a data warehouse and plan for implementing it into your business operation. And you'll examine the considerations and best practices for implementing and utilizing edge computing in your organization.