An Implementation Guide To Analytic Lifecycle Management

Agile by Design: An Implementation Guide to Analytic Lifecycle Management (Wiley and SAS Business Series)

by Rino Di Stefano

4.5 out of 5

Language	:	English
File size	:	10070 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	254 pages
Lending	:	Enabled

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Analytic lifecycle management (ALM) is a process that helps organizations to manage the entire lifecycle of their analytic assets, from data collection and preparation to model development and deployment. By following an ALM process, organizations can ensure that their analytic initiatives are aligned with their business goals, that they are using the right data and tools, and that they are getting the most value from their analytic investments.

The Benefits of ALM

There are many benefits to implementing ALM, including:

• Improved data quality and consistency
• Reduced time to market for analytic initiatives
• Increased accuracy and reliability of analytic results
• Improved collaboration between data scientists and business users
• Reduced risk of analytic failure

The ALM Process

The ALM process consists of five key steps:

1. Planning and assessment: This step involves defining the goals of your analytic initiative, identifying the data and tools that you will need, and assessing your current capabilities.
2. Data collection and preparation: This step involves collecting the data that you will need for your analytic initiative and preparing it for analysis.
3. Model development and deployment: This step involves developing and deploying the analytic models that you will use to make predictions or recommendations.
4. Monitoring and evaluation: This step involves monitoring the performance of your analytic models and evaluating their impact on your business.
5. Governance: This step involves establishing policies and procedures for managing your analytic assets and ensuring that they are used in a responsible and ethical manner.

Implementing ALM in Your Organization

Implementing ALM in your organization can be a challenge, but it is a worthwhile investment. By following the steps outlined in this guide, you can increase the success of your analytic initiatives and get the most value from your data.

Here are some tips for implementing ALM in your organization:

• Start small and scale up: Don't try to implement ALM for your entire organization all at once. Start with a small project and gradually expand your scope as you gain experience.
• Get buy-in from leadership: It is important to get buy-in from leadership before implementing ALM. Make sure that they understand the benefits of ALM and are committed to supporting it.
• Build a team of experts: You will need a team of experts to implement ALM in your organization. This team should include data scientists, data engineers, business analysts, and IT professionals.
• Use the right tools: There are a number of tools available to help you implement ALM. Choose the tools that best fit your needs and budget.
• Monitor and evaluate your progress: It is important to monitor and evaluate your progress as you implement ALM. This will help you to identify areas where you can improve and ensure that you are getting the most value from your investment.

ALM is a powerful tool that can help organizations to get the most value from their data. By following the steps outlined in this guide, you can implement ALM in your organization and improve the success of your analytic initiatives.

Agile by Design: An Implementation Guide to Analytic Lifecycle Management (Wiley and SAS Business Series)

by Rino Di Stefano

4.5 out of 5

Language	:	English
File size	:	10070 KB
Text-to-Speech	:	Enabled
Screen Reader	:	Supported
Enhanced typesetting	:	Enabled
Word Wise	:	Enabled
Print length	:	254 pages
Lending	:	Enabled

FREE