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Showing posts from September, 2024

Effective Strategies for Program Managers to Manage Scope Creep and Requirement Changes

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  Introduction : As a Program Manager, managing scope creep and requirement changes is essential to maintaining project timelines, quality, and stakeholder satisfaction. This presentation outlines key strategies and best practices for handling scope creep and change requests effectively, while keeping your team motivated and delivering consistent results. Conclusion Managing scope creep and requirement changes is a critical skill for any program manager. By identifying the reasons for scope changes, adhering to a clear change management process, holding regular triage meetings, and educating your team, you can control scope while staying adaptable. Remember that scope creep is often unavoidable, but with proper planning, communication, and team engagement, it can be managed without disrupting the project’s success. Keep your team motivated, keep stakeholders informed, and balance flexibility with focus to deliver successful projects. My LinkedIn reference: https://www.linkedin.com/...

How Sharding a database can make it faster and Solutions for Data inconsistencies in a database

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  Introduction In today's data-driven world, managing and scaling databases efficiently is crucial for handling large volumes of data and ensuring fast response times. One effective strategy for improving database performance is sharding , a technique that partitions data into smaller, more manageable chunks across multiple servers. In this article, we’ll explore how sharding can make databases faster and discuss common solutions to handle data inconsistencies that can arise in sharded systems. What is Database Sharding? Database sharding is a system design technique where a large database is split into smaller pieces called shards . Each shard operates as an independent database, holding only a subset of the entire dataset. By distributing the data across multiple shards, organizations can balance the load and reduce the performance bottlenecks typically encountered when querying massive datasets. It is basically a database architecture pattern in which we split a large datase...