Aspire Journeys

Data for Leaders and Decision-makers

  • 25 Courses | 17h 50m 27s
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The Data for Leaders and Decision-makers journey is designed to raise the awareness of managers, leaders, and decision-makers on data and modern data technologies. It gives a comprehensive view of modern data sources, modern data infrastructures and groundbreaking technologies, that are emerging for addressing a wide range of business needs. This course focuses on widely adopted data technologies, tools, frameworks, and platforms at a high level for enabling the managers and leaders to comfortably get engaged in data projects. Learners will also understand everything about data, various data compliance issues, data governance, and various data strategies to be adopted for making better data-driven decisions that are critical for the business.

Track 1: Data Primer

In this track of the Data for Leaders and Decision-makers Skillsoft Aspire journey, the focus will be on the fundamentals of data, traditional data architectures, and new age data infrastructures.

  • 5 Courses | 2h 36m 27s

Track 2: Big Data Infrastructures

In this track of the Data for Leaders and Decision-makers Skillsoft Aspire journey, the focus will be on big data concepts, non-relational data, and big data analytics.

  • 6 Courses | 3h 47m 7s

Track 3: Raw Data to Insights

In this track of the Data for Leaders and Decision-makers Skillsoft Aspire journey, the focus will be on data mining and decision making.

  • 4 Courses | 2h 48m 28s

Track 4: Emerging New Age Architectures

In this track of the Data for Leaders and Decision-makers Skillsoft Aspire journey, the focus will be on cloud data platforms, data lakes, and modern warehouses.

  • 6 Courses | 5h 10m 35s

Track 5: Data Governance and Management

In this track of the Data for Leaders and Decision-makers Skillsoft Aspire journey, the focus will be on modern data management.

  • 4 Courses | 3h 27m 50s


Data Nuts & Bolts: Fundamentals of Data
Dealing with large amounts of data is essential to any modern business and to become a data-driven organization, leaders and decision-makers must establish a deeply ingrained data culture. Use this course to understand the underlying principles of analyzing data and get familiar with terms related to data in order to properly deliver data-related projects. This course will help you identify the basic concepts and processes related to data analysis, modern data sources, and data pipelines. You'll also discover fundamental principles of data storage, migration, and integration, along with common methods for data visualization and reporting. Having completed the course, you'll be well versed in foundational concepts of data, related terminologies, and various data processing methods.
10 videos | 33m
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Traditional Data Architectures: Relational Databases
Databases are essential in working with large amounts of data. Managers, leaders, and decision-makers need to choose the right approach when working on a large data project, distinguishing among multiple database types and their use cases. A relational database is a primary traditional data architecture commonly used by most businesses. Working with relational databases has some key advantages but also poses certain limitations. In this course, learn how critically evaluate and work with relational databases. Explore normalization and denormalization of datasets along with specific use cases of these opposite approaches. Examine two main online information processing systems, Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP) systems. Finally, investigate the concepts of data warehousing, data marts, and data mining. Upon completion, you'll be able to identify when and how to use a relational database.
12 videos | 39m
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Traditional Data Architectures: Data Warehousing and ETL Systems
Data warehouses are actively used for business intelligence and, because they integrate data from multiple sources, are advantageous to simple databases in many instances. Considering modern companies often have ETL-based data warehousing systems, decision-makers need to comprehend how they operate and are appropriately managed. In this course, learn the necessary concepts and processes required to work with and manage projects related to data warehousing. Study data warehousing architectures and schemas and investigate some core data warehouse elements, such as dimension, fact tables, and keys. Furthermore, examine the extract, transform, and load (ETL) approach for working with data warehouses, specifying process flow, tools, and software as well as best practices. When you're done, you'll know how to adopt data warehousing and ETL systems for your business intelligence and data management needs.
12 videos | 43m
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New Age Data Infrastructures: Factors Driving Data Infrastructures
As technology advances, new ways to store, process, and analyze data emerge. For example, large database systems, which require a lot of storage space, have been moved to the cloud and made remotely accessible to many users. These kinds of data infrastructures require business leaders to understand modern data systems and their working principles fully. Use this course to get to grips with the key differences between legacy data systems and modern infrastructures and explore crucial concepts related to modern data infrastructures. By the end of the course, you'll be able to argue why new age data infrastructures are necessary and traditional data systems are limited.
12 videos | 38m
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Big Data Concepts: Getting to Know Big Data
Big data analytics has become an essential part of any business dealing with the digital world. The ability to collect large amounts of data and turn it into insights has transformed the world's business landscape. To properly manage projects using such technologies, leaders should at least have a foundational understanding of big data. Use this course to get to grips with the necessary concepts and terminologies you'll need when discussing big data projects. Learn about the primary sources and characteristics of big data. Then, dive into the world of big data analytics - exploring its main advantages, use cases, and significant challenges. When you've finished this course, you'll be able to speak about data-related projects, discussing relevant data infrastructures and architectures confidently.
12 videos | 43m
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Big Data Concepts: Big Data Essentials
Big data analytics, collecting vast amounts of data and transforming it into insights, drives major business decisions everywhere. Managers, decision-makers, data technicians, and data enthusiasts alike benefit from knowing how various systems and technologies are used in big data projects. Use this course to progress from a foundational comprehension of big data analytics to grasping more advanced concepts, like parallel and distributed computing systems and horizontal and vertical scaling. Take an in-depth look at Hadoop's main components and characteristics and how it's used for big data analytics. Then, delve into the various kinds of storage systems used in big data. Upon completing this course, you'll have a greater comprehension of the tools and methods used to execute big data projects.
12 videos | 45m
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Non-relational Data: Non-relational Databases
Non-relational (NoSQL) databases are attractive for working with Big Data because they provide a way to store data from different sources in the same document and organize large amounts of diverse and complex data. Use this course to discover the principles behind non-relational databases and NoSQL, explore their benefits, and examine different types of non-relational architectures, such as document, key-value, graph, columnar, and multi-model databases. You'll also get familiar with HBase and NewSQL. After finishing this course, you will be able to identify the suitable NoSQL database required for any given business problem. 
12 videos | 46m
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Techniques for Big Data Analytics
Big data analytics provides a way to turn the vast amounts of data available in today's digital world into valuable insights. For this reason, big data analytics techniques have taken a central place in many businesses' IT infrastructure. These comprise complex processes and multiple stack layers that allow you to transform raw data into visualizations that demonstrate trends or other phenomena. Use this course to explore the basic principles and techniques of big data analytics in a business context. Go through each step of data processing to fully comprehend the big data analytics pipeline. Furthermore, explore various use cases of big data analytics through real-world examples. When you're done with this course, you'll have a foundational comprehension of some of the technologies behind big data and how these can drive business decisions for the better.
12 videos | 34m
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