Structured along the Data Analytics lifecycle, we'll share hidden gems that will save you time.

To become a Data Ninja we'll share hidden gems that will save you time:

1. What’s new with SAS Programming?
2. Latest programming interfaces & tricks.
3. Data Import tips & techniques.
4. Data preparation best practices.
5. SAS Processing & Code optimisation.
6. Integration with Open Source.
7. Deep-dives on Graphs, reporting and Data Analysis.

Have a sneak peek how the first step of your journey looks like

このプログラムでは、コーダー (プログラマー) やアナリスト、データ サイエンティストが迅速にSAS Viya エキスパートになるためのJourney を提供します。

以下のJourneyで迅速にSAS Viyaエキスパートになる

1. Viya が他と異なる理由、それがどう役立つか
2. SAS 9 コードとプロジェクトの移行
3. データ準備の改善点
4. レポート、ダッシュボード、データ探索でさらに強化された点
5. Viyaとオープンソースの統合
6. Viyaで高度な機械学習から始める

Journey初期のプレビューはこちらをご覧ください (英文)。

お届けするコンテンツには英語のものもあります。ブラウザや動画サイトの自動翻訳・キャプション機能をご利用ください。

Topics in this journey include:

1. Viya architectural principles.
2. Top Viya Admin tasks.
3. Security in Viya.
4. Diagnosing Performance Issues.
5. Cloud & Container deployments.

Have a sneak peek how the first step of your journey looks like

If you think you've only scratched the surface of SAS Visual Analytics, this is the perfect fast-track.

Topics in this journey include:

1. Data Storytelling concepts.
   
2. Preparing data in SAS Visual Analytics.
3. Creating interactive reports.
   
4. Telling a story through a dashboard.
   
5. Using advanced analytics to develop models.
6. Geo-location data in dashboards.
   
7. Sharing your insights.

Have a sneak peek how the first step of your journey looks like

This journey helps you optimize your AML scenarios with advanced analytics & techniques.

In this programme, you’ll learn using SAS Analytics & AML tools to:

1. Improve your AML Strategies to reduce false positives.
2. Tune AML scenarios and prioritise alerts.
3. Introduce AI & Machine Learning into your AML use cases.
4. Prepare for the future of AML using SAS.

Have a sneak peek how the first step of your journey looks like

With our onboarding programme, we’ll orientate you on how to find the best services, expert advice and learning tools - those resources which have proven popular with SAS users like you.

To assist you in the early days of your SAS use, this journey will share a number of resources that will provide you with inspirational resources, such as:

1. Effective ways to jump-start your learning experience.
2. Best practices and hands-on tips and tricks from savvy experts.
3. Multiple ways to leverage our support resources.
4. How to engage with other (new) SAS users in a worldwide community network.
5. Our ambassador program for novice SAS users and seasoned specialists.

If you're looking for ways to detect and prevent new fraud typologies, this journey will give you insights for developing better fraud prevention strategies, reducing false positives and improving your investigations. This journey is mostly aimed at customers using SAS Fraud Management (SFM).

In this seven-step programme, you will learn about Next Generation Fraud Detection in Banking.

1. Understanding Fraud Trends
2. Understanding Fraud Trends (Part 2)
3. Basics of Fraud Detection Strategies
4. Building Fraud Detection Strategies (Part 2)
5. Analyse and Investigate Alerts
6. Improve Investigations
7. Plug-In Fraud Analytics to detect complex frauds

Have a sneak peek how the first step of your journey looks like

From the fundamentals of the Data Scientist role to advanced Machine Learning, we'll take you on a journey on what you need to know to succeed as a SAS Data Scientist.

1. The role of a Data Scientist
2. Developing the skills you need
3. Modern Feature Engineering in SAS
4. Advanced Statistical Techniques in SAS
5. Machine Learning in SAS
6. Using Open Source with SAS
7. Advanced AI & Text Analytics with SAS
8. Advanced Machine Learning with SAS

Have a sneak peek how the first step of your journey looks like

Learn how to automate your SAS code and data lifecycle with GIT, Jenkins and DevOps principles.

This journey is structured around the DevOps lifecycle and CI/CD principles:

1. Planning
2. Code development and management
3. Build with APIs
4. Test Automation
5. Release and artifact repository
6. Deployment
7. Release and monitoring

Have a sneak peek how the first step of your journey looks like

Our journey focuses on the applicability of advanced techniques like Machine Learning to the Credit Risk landscape.

1. Artificial Intelligence in Risk
2. AI and Regulatory Compliance
3. Machine Learning in Credit Risk
4. New Challenges on Data Preparation
5. Modelling for Debt Collection
6. Intelligent Credit Decisioning
7. Climate Risk Modeling

Have a sneak peek how the first step of your journey looks like