Analytics Store Training

The Analytics Store has been providing training, mentoring and consultancy services in the field of Data Analytics since 2009. Being both educators and practitioners in this field provides the team at The Analytics Store with unique insights into the challenges faced by analytics teams. At a time when demand is growing and when businesses are faced with a skills shortage in the area, we believe that the old approach of simply providing a one-off course is no longer enough. Teams need to be upskilled in relevant areas, and busy managers require support to ensure that learnings are embedded and applied as quickly and consistently as possible.

Rather than simply deliver a course, The Analytics Store works closely with its clients to understand their business requirements and objectives, and to tailor skills-based development programmes to meet the needs of the organisation, team and individuals within. We have a range of established and proven courses at beginner, intermediate and advanced levels. Custom courses and programmes can also be created from scratch upon request – for example, using specific technology, aimed at exec teams, including additional workshops or designed to align to our clients’ graduate training schemes. Each course and training plan takes into account Theory, Tools and Application. Each are approached separately and blended together in a way that means learnings can be confidently applied once back in the workplace, and easily transferred as technologies change.

For more information on our courses, or to discuss bespoke training, please contact info@theanalyticsstore.com.

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Technology Used

Training Courses

Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R and python languages are some of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions.

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Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. These programming languages are some of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates who are already familiar with analytics techniques and at least one programming language how to effectively use the programming language for three tasks: data manipulation and preparation, statistical analysis and advanced analytics (including predictive modelling and segmentation). Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions.

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The most effective businesses make their decisions based on data and evidence, rather than unfounded gut feelings. This course covers the statistical methods that analysts need to move from simple reporting on business problems to extracting insight to solve business problems. Delegates will learn how to use modern data analytics tools to generate descriptive statistics, perform statistical testing and build statistical models. On returning to work after completing this course delegates will immediately be able to make a difference to the way that their organisations make decisions.

Read More
The companies using analytics most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data.

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So, you’ve learned about the power of analytics and advanced analytics techniques, but are you getting the most out of your data? Using examples from customer segmentation to sales forecasting, this course demystifies the techniques required to transform raw data into insight-filled data for driving your analytics solutions.

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The use of analytics is widespread in business and for those without analytics training running analytics projects and building analytics teams can be daunting. This short, focused course will explain how analytics can be used in an organisation, how to run and manage an analytics project, and how to build a successful analytics team.

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Predictive analytics applications use machine learning to build predictive models for applications including price prediction, risk assessment, and predicting customer behaviour. Based on the trainers’ book, “Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies” (www.machinelearningbook.com) this course presents a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

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Many business needs in the realm of analytics can be addressed using network analysis.  Examining data for communities or matrices of co-occurring elements, events or people can be useful in detecting items as diverse as influencers, fraud and communities of buyers.  This course provides in-depth exposure to techniques that can be used to model networks within data.

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Project management is an in-depth skill that is required in all aspects of business. Analytics projects have their own challenges demanding an analytics-oriented project management approach. This course describes good general project management practice and methodologies. It then focuses on providing the scaffolding for analytics project management specifically. It will introduce our Agile Analytics Framework which incorporates elements of Problem Solving, Agile and CRISP-DM methodologies to ensure that every data project delivers positive business impact.

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This course is for users who want to learn how to write SAS programs. It is the entry point to learning SAS programming and is a prerequisite to many other SAS courses. If you do not plan to write SAS programs and you prefer a point-and-click interface, you should attend the SAS Enterprise Guide 1: Querying and Reporting (EG7.1) course.

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This course is for those who need to learn data manipulation techniques using SAS DATA and procedure steps to access, transform, and summarize SAS data sets. The course builds on the concepts that are presented in the SAS Programming 1: Essentials course and is not recommended for beginning SAS software users.

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This course is for SAS programmers who prepare data for analysis. The comparisons of manipulation techniques and resource cost benefits are designed to help programmers choose the most appropriate technique for their data situation.

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This training is appropriate for SAS Enterprise Miner 14.1. This course covers the skills that
are required to assemble analysis flow diagrams using the rich tool set of SAS Enterprise Miner for both
pattern discovery (segmentation, association, and sequence analyses) and predictive modeling (decision
tree, regression, and neural network models).

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This course focuses on the components of the SAS macro facility and how to design, write, and debug macro systems. Emphasis is placed on understanding how programs with macro code are processed.

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This course is for users who do not have SAS programming experience but need to access, manage, and summarize data from different sources, and present results in reports and graphs. This course focuses on using the menu-driven tasks in SAS Enterprise Guide, the point-and-click interface to SAS, to create queries and reports. It does not address writing SAS code or statistical concepts. This course serves as a prerequisite for the SAS Enterprise Guide 2: Advanced Tasks and Querying (EG 7.1) course and for the Creating Reports and Graphs with SAS Enterprise Guide course. It also serves as a prerequisite for the SAS Enterprise Guide: ANOVA, Regression, and Logistic Regression (EG 7.1) course, which teaches statistical concepts using SAS Enterprise Guide.

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The use of analytics, statistics and data science in business has grown massively in recent years. Harnessing the power of data is opening actionable insights in diverse industries from banking to horse breeding.  Organisations spend a huge amount of recourses applying business intelligence and advanced analytics techniques to uncover these insights. Organisations doing this most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations, reports and dashboards from data using SAS Visual Analytics.

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Machine learning and predictive data analytics are fast becoming the best way for sophisticated organisations to use data to gain a competitive edge. Predictive analytics applications use machine learning to build predictive models for applications including price prediction, risk assessment, and predicting customer behaviour. Based on the trainers’ book, “Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies” (www.machinelearningbook.com) this course presents a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

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Overview: This course is a boot camp that covers the content of both SAS Data Integration Studio: Essentials and SAS Data Integration Studio: Additional Topics. It introduces and expands the knowledge of SAS Data Integration Studio and includes topics for registering sources and targets; creating and working with jobs; and working with transformations. This course also covers information on working with slowly changing dimensions, working with the Loop transformations, and defining new transformations.

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Overview: This course is intended for experienced SAS Enterprise Guide users who want to learn more about advanced SAS Enterprise Guide techniques. It focuses on using the Query Builder within SAS Enterprise Guide, including manipulating character, numeric, and date values; converting variable type; and building conditional expressions using the Expression Builder. This course also addresses efficiency issues, such as joining tables and using a single query to group, summarize, and filter data.

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This course provides students with the essential knowledge to perform the job functions of a SAS platform administrator.

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Overview: This course is designed as the first step for those who want to use JMP to manage, analyze, and explore data. Two case studies will be used to present typical data analysis issues that our students see. (The ecourse will have the same general content but with a different format.)

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Overview: This course teaches how to analyze data with a single continuous response variable using analysis of variance and regression methods. You learn how to perform elementary exploratory data analysis (EDA) and discover natural patterns in data. Important statistical concepts such as confidence intervals are also introduced.

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Overview: This course teaches how to explore data and build reports using SAS Visual Analytics. You will learn how to build queries in SAS Visual Data Builder and you will also learn the basics of SAS Visual Analytics Administrator.

Pre-requisites: No SAS experience or programming experience is required, although you should have some computer experience.

Specifically, you should

  • be able to log on and off a computer and use a keyboard or mouse
  • know how to use a Web browser to access information.

This course addresses SAS Visual Analytics software

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Analytics Fundamentals

The most effective businesses make their decisions based on data and evidence, rather than unfounded gut feelings. This course covers the statistical methods that analysts need to move from simple reporting on business problems to extracting insight to solve business problems. Delegates will learn how to use modern data analytics tools to generate descriptive statistics, perform statistical testing and build statistical models. On returning to work after completing this course delegates will immediately be able to make a difference to the way that their organisations make decisions.

Read More

Becoming a world class data analytics practitioner requires mastery of the most sophisticated data analytics tools. The R and python languages are some of the most powerful and flexible tools in the data analytics toolkit. This course teaches delegates with no prior programming or data analytics experience how to perform data manipulation, data analysis and data visualisation. Mastery of these techniques will allow delegates to immediately add value in their work place by extracting valuable insight from company data to allow better, data-driven decisions.

Read More

The use of analytics is widespread in business and for those without analytics training running analytics projects and building analytics teams can be daunting. This short, focused course will explain how analytics can be used in an organisation, how to run and manage an analytics project, and how to build a successful analytics team.

Read More

The companies using analytics most successfully understand that using sophisticated analytics approaches to unlock insights from data is only half the job. Communicating these insights to all of the different parts of an organisation is just as important as doing the actual analysis. Visualising data, and analytics results, is one of the most effective ways to achieve this. This course will cover the theory of data visualisation along with practical skills for creating compelling visualisations from data.

Read More

Advanced Analytics

Predictive analytics applications use machine learning to build predictive models for applications including price prediction, risk assessment, and predicting customer behaviour. Based on the trainers’ book, “Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples and Case Studies” (www.machinelearningbook.com) this course presents a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.

Read More
Many business needs in the realm of analytics can be addressed using network analysis.  Examining data for communities or matrices of co-occurring elements, events or people can be useful in detecting items as diverse as influencers, fraud and communities of buyers.  This course provides in-depth exposure to techniques that can be used to model networks within data.

Read More

Time series data arises in applications from finance to personal activity monitoring and has unique characteristics that demand the use of specialised techniques. The course covers the fundamentals of modelling time series data and focuses on the application of the main model types used to analyse univariate time series: simple linear regression, exponential smoothing and autoregressive integrated moving average with exogenous variables (ARIMAX). This course can be delivered in R, Python, or SAS.

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While many machine learning tasks, such as propensity modelling, have become standardised to the point of near automation, detecting anomalies in large complex datasets remains a fundamental challenge often requiring bespoke, creative solutions. There are, however, a core set of techniques and design patterns that can be built upon for anomaly detection problems in domains such as fraud detection, risk identification, and classification of rare events. Through presentations, real world examples, discussions, and workshops this workshop introduces the most important of these. This course can be delivered in R, Python, or SAS.

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This course focuses on applying natural language processing tools and techniques to extract insights from large collections of text data. It has been designed to guide delegates through the most important topics in NLP, and how they should be applied to build real-world-relevant solutions. This course is delivered in Python.

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This course focuses on using machine learning techniques based on large artificial neural networks to perform prediction and generation tasks. These are often referred to as deep learning models and their introduction in recent years, coupled with advances in computational hardware and the scale of datasets currently available to us, has led to step changes in the performance of machine learning models. This course has been designed to guide delegates through the most important topics in deep learning, and how they should be applied to build real-world-relevant solutions. This course is delivered in Python.

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This foundation course in Spark and Scala is designed for experienced programmers working on big data projects who need to broaden their skill set with Spark and Scala. It will provide a solid introduction into the Scala programming language and Spark, along with practical workshops designed to ensure delegates leave able to apply learnings in “real-world” scenarios.

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Applying Analytics

Project management is an in-depth skill that is required in all aspects of business. Analytics projects have their own challenges demanding an analytics-oriented project management approach. This course describes good general project management practice and methodologies. It then focuses on providing the scaffolding for analytics project management specifically. It will introduce our Agile Analytics Framework which incorporates elements of Problem Solving, Agile and CRISP-DM methodologies to ensure that every data project delivers positive business impact.

Read More

Part of the challenge facing Data Analytics teams is how to engage and influence the wider organisation around them. Internal customers don’t always know quite what to ask for, and it’s easy to get carried away focusing on what you think they need. This workshop is designed to support individuals and teams in how best to interact with each other and the organisation around them using sound problem solving and project management skills alongside an awareness of stakeholder management and communication.

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SAS Training Partnership

The Analytics Store is proud to partner with SAS. Having worked closely over the last 15 years in developing and delivering SAS training all over Europe, The Analytics Store are delighted to be the only approved training partner for SAS UK and Ireland.