Evaluating Options for Data Platform Implementation PPT

This PPT slide, part of the 27-slide Pathways to Data Monetization PowerPoint presentation, outlines 4 distinct options for establishing a Data Platform: Build, Buy, Lease, and Partner. Each option is presented with its strengths and limitations, offering a clear comparison to aid decision-making.

The "Build" option emphasizes customization, highlighting that in-house solutions can be tailored to meet specific organizational needs. It notes the importance of cybersecurity and control, which can be critical for sensitive data handling. However, the slide points out that this approach typically demands significant investment in technology infrastructure and talent, making it the most expensive choice.

The "Buy" option is characterized as a cost-effective alternative to building from scratch. It allows organizations to leverage off-the-shelf solutions that can be enhanced with in-house development. While this method can meet strategic needs, it also requires a comprehensive understanding of the software's functionalities and limitations, which can be a considerable commitment.

"Lease" is presented as a flexible option, with a shorter commitment period and a variety of tech solutions available. This approach allows organizations to avoid heavy upfront investments and vendor management complexities. However, it warns that leased solutions may not fully align with specific requirements and can lead to operational challenges due to vendor proliferation.

Lastly, the "Partner" option offers a balance between commitment and customization. It allows for tailored solutions without the heavy investment of building or leasing. Yet, it requires effective vendor management and an understanding of market intelligence capabilities.

Overall, the slide encourages a careful evaluation of each option, emphasizing the need for a strategic approach to budgeting and decision-making regarding data platforms.

This slide is part of the Pathways to Data Monetization PowerPoint presentation.

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Analytics Data & Analytics Data Monetization Market Intelligence Vendor Management Cybersecurity

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