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Last updated on 2024年9月19日

How do you manage the complexity and diversity of workflows in your analytics environment?

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Analytics workflows are the sequences of steps, tasks, and tools that transform raw data into meaningful insights. They can vary widely in complexity, diversity, and scope, depending on the data sources, business objectives, analytical methods, and stakeholder needs. Managing multiple workflows in your analytics environment can be challenging, but also rewarding. Here are some tips to help you optimize your workflow management and achieve better results.

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Define clear workflow goals:

Start by identifying what you aim to achieve with each workflow and communicate these goals to your team. This helps align efforts with business strategies, ensuring everyone stays focused and motivated.### *Select optimal tools:Choose tools and platforms that best match your data types and analytical needs. This streamlines processes, enhances collaboration, and improves overall efficiency in managing diverse workflows.

本摘要由 AI 和以下专家提供支持

Sandana Thevar (Sandy) DMS

Product Manager @ Enate | 20x LinkedIn…
Doha Shawki , MBA, CPOA

Information Technology Services Manager…

1 Define your workflow goals

Before you start any workflow, you need to have a clear idea of what you want to accomplish, why, and how. This will help you align your workflow with your business strategy, prioritize your tasks, and measure your progress. You should also define your workflow scope, inputs, outputs, and deliverables, and communicate them to your team and stakeholders. Having a well-defined workflow goal will keep you focused and motivated throughout the process.

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Harley Martin

Operational Excellence / Business Process
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I couldn’t agree more with everything stated above. Plus, know you audience… what I mean know the level of details to provide and choice to use acronyms or not. Also keep in mind workflows are a ever growing document. So you must maintain the Standard Operating Procedures (SOPs) from time to time.

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Doha Shawki , MBA, CPOA

Information Technology Services Manager - City of Toronto
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Totally agree, I want to add as well that yes you start with the Business goal. Then you ask why am I doing this, what are we trying to achieve. The next step would be what are we measuring? SLAs, KPIs, OKRs,.. those have to be defined before deciding on the workflow. And lastly you will go to the how?

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2 Choose the right tools and platforms

The tools and platforms you use for your analytics workflows can make a big difference in your efficiency, quality, and collaboration. You should select the tools and platforms that best suit your data types, analytical techniques, and workflow requirements. For example, you might use a cloud-based platform for scalable data storage and processing, a data integration tool for connecting and transforming data from different sources, a data visualization tool for creating interactive dashboards, and a workflow orchestration tool for automating and monitoring your tasks.

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Sandana Thevar (Sandy) DMS

Product Manager @ Enate | 20x LinkedIn Top Voice | Lean Six Sigma Master Black Belt??| CAPM??| Scrum Certified? | Agile | Risk Management | ISO 9001:2015 | Data Science | Design Thinking | Product Design & Development
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To manage the complexity and diversity of workflows in my analytics environment, I focus on choosing the right tools and platforms that can handle various data sources and tasks efficiently. I ensure the tools are flexible enough to integrate seamlessly and scalable to meet evolving needs. This helps streamline workflows, making it easier to manage data, collaborate, and derive insights without getting bogged down by technical limitations. The right platforms make a significant difference in simplifying processes and improving overall efficiency.

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3 Design your workflow logically and flexibly

A good workflow design should follow a logical and flexible structure that allows you to perform your tasks smoothly and effectively. You should break down your workflow into manageable steps, assign roles and responsibilities, and document your methods and assumptions. You should also consider the dependencies, contingencies, and risks that might affect your workflow, and plan accordingly. A good workflow design should also be adaptable to changing data, business, and user needs, and allow you to iterate and improve your workflow over time.

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Doha Shawki , MBA, CPOA

Information Technology Services Manager - City of Toronto
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I would like to add that workflows need to be reviewed to make sure it doesn't contain redundancies. Too many back and forth activities make it inefficient. Also it should be optimized with a clear triggering point and ending point to ensure it is flexible enough if business needs change and the workflow needs updating

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4 Test and validate your workflow results

Testing and validating your workflow results are essential steps to ensure the accuracy, reliability, and relevance of your analytics insights. You should test your workflow at different stages, such as data quality, data transformation, data analysis, and data visualization, and use appropriate methods and metrics to verify your results. You should also validate your results with your stakeholders, and solicit their feedback and suggestions. Testing and validating your workflow results will help you avoid errors, biases, and inconsistencies, and enhance your credibility and trustworthiness.

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5 Share and reuse your workflow assets

Sharing and reusing your workflow assets can help you save time, resources, and effort, and foster a culture of collaboration and learning in your analytics environment. You should document and store your workflow assets, such as data sets, code, scripts, models, reports, and dashboards, in a centralized and accessible location, and use standard formats and naming conventions. You should also share your workflow assets with your team and other users, and encourage them to reuse and modify them for their own purposes. Sharing and reusing your workflow assets will help you leverage your existing knowledge and skills, and create new value and opportunities.

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6 Review and optimize your workflow performance

Reviewing and optimizing your workflow performance is a continuous process that helps you identify and address the strengths and weaknesses of your analytics workflows. You should monitor and measure your workflow performance using relevant indicators, such as speed, quality, cost, impact, and satisfaction. You should also analyze and compare your workflow performance with your goals, expectations, and benchmarks, and identify the gaps and areas for improvement. You should then implement the necessary changes and enhancements to your workflow design, tools, methods, and results, and evaluate their effects. Reviewing and optimizing your workflow performance will help you achieve higher levels of efficiency, quality, and value in your analytics workflows.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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How do you manage the complexity and diversity of workflows in your analytics environment?

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1 Define your workflow goals

2 Choose the right tools and platforms

3 Design your workflow logically and flexibly

4 Test and validate your workflow results

5 Share and reuse your workflow assets

6 Review and optimize your workflow performance

7 Here’s what else to consider

Workflow Management

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