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Open Source Software Versus Proprietary Software – An Insight

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Legacy Application Modernization Removes All Business Obstacles Caused by Inefficient Legacy Applications Read All About Legacy Application Modernization Given the central role of digital technology in many industries, the social sector is embracing Open Source Software (OSS). ) has benefited greatly. In 2020, GitHub, the world’s largest software development platform, tracked more than 1.9 billion contributions to projects, representing a 25% increase in open source repositories from 2019. The proliferation of OSS provides an opportunity for social sector leaders and practitioners to innovate and collaborate using digital technology, offering new alternatives to proprietary software.

What Is Open Source Software? The Definitive Guide

When choosing new digital technologies – especially those required to manage, analyze and transform data – professionals in the social sector are often faced with the decision of whether to choose an OSS solution over a property. Many data workflows have useful and popular OSS alternatives to proprietary tools. For example, a data analyst may use proprietary visualization tools, and open source packages, such as ggplot2 in g or R, ArcGIS or an OSS equivalent. Monitoring and evaluation (M&E) professionals need to choose between. In this case of QGIS, a geographic information system, there are many factors to consider, in addition to software cost or available features, among others. Rather, the decision to choose an OSS versus a proprietary solution is arbitrary and must be carefully weighed

This introductory guide explores the nuances, common trade-offs, applicable costs, and security and privacy concerns that are common when evaluating OSS versus proprietary software. The purpose of this introductory guide is to provide professionals in the social sector, such as M&E professionals, data analysts, software engineers, among others, with an overview of potential trade-offs. Managed Online Below we provide a summary of our methodology and analysis, a high-level summary of our findings, and a framework for evaluating OSS versus proprietary solutions.

To understand the potential trade-offs when evaluating OSS versus proprietary software in terms of information, this introductory guide takes a three-pronged approach. First, desk research was conducted to build a knowledge base and broadly understand the trade-offs between OSS and proprietary solutions. Next, a survey was designed and distributed through a professional network of program managers, data analysts, M&A professionals, and software developers. The survey (n = 24) captured both quantitative and qualitative responses to common barriers and considerations that practitioners receive when evaluating OSS and proprietary software. Using these responses as a guide, semi-structured interviews were conducted with data scientists (n = 1), software engineers (n = 3), and monitoring and evaluation specialists (n). n = 6) was performed with . = 3). By triangulating this data with survey responses and desk research, the team conducted descriptive analysis to identify common themes and common barriers when evaluating OSS and proprietary software.

In this introductory guide, OSS is broadly defined as software that is freely distributed and uploaded to an accessible repository that provides source code. In particular, code, data, or content must be subject to an open source license, provided that the code base is freely available (see Open Source Initiative for more details and definition). Proprietary software, on the other hand, is copyrighted, because restrictions against use, distribution, and/or modification are imposed by the copyright holder. In addition, software development licensing also has a sustainable business model known as open house. That is, open source is generally known as a monetization of commercially produced OSS, adding properties that provide additional features that come with a commercial license. Examples of open source software include many products as a service (SaaS) such as Kafka, a data streaming service under Apache 2.0, Oracle’s MySQL database, Neo4j with enterprise add-ons under a commercial license. To get an idea of ​​the range of differences between OSS, open source, and proprietary software, see Figure 1:

Custom Open Source Vs Proprietary Software [infographics]

When evaluating OSS and proprietary software, four considerations were identified in the results of interviews and surveys. In particular, experts maintain that software interoperability—the ability to “understand” their solutions and work with other software—is essential given the cross-functional work of multiple teams. Cost was also an important issue, as it relates not only to the cost of the solution but also to the indirect and opportunity costs associated with building, deploying and managing the solution. However, getting support for these decisions requires leadership buy-in and a mature data organization, which is critical to improving and improving data-related operations. Therefore, ethical and legal considerations must also be followed. For a summary of the findings, see Table 1

Ability to “understand” a software product or system and work with other software solutions for long-term implementation and performance.

Costs, direct or indirect, that may occur at any time during the software solution’s life cycle, including equipment purchases, labor costs, opportunity costs during solution development, deployment or maintenance.

Support and general ability within an organization and leadership to develop and improve data-related activities, including but not limited to data quality, skills, culture, applications, etc.

Proprietary Vs Open Source: The Software Dilemma

Adhere to ethical and legal considerations, such as data protection and privacy policies (eg, GDPR, HIPAA, etc.), design and community accountability, among others.

The first consideration was that practitioners evaluated their decisions regarding the compatibility of their solutions with other proprietary solutions or OSS tools. That is, interoperability – defined as the ability of a software product or system to understand and work with other software solutions – played a key role in choosing sustainable and effective products. For example, do the solutions recognize common data formats and communication protocols and be able to communicate with each other? Can you save the data in another format (for example, a csv file), which you can share with other team members? Can the solution be used by multiple partners and groups?

“If I consider open source products, I use Airtable or Excel/PowerB,

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