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Assembling the perfect data stack isn’t easy. The most valuable ones allow companies to take advantage of rapidly evolving technology, adding best-of-breed solutions for collecting, transforming, and analyzing data without requiring a large commitment of time and money. But too many companies see their plans for improvement impeded by the pitfalls of a monolithic, legacy applications, and outdated architecture.
To stay competitive, data teams must learn to modernize their data architecture without overspending on costly implementations, falling victim to vendor lock-in, or diverting engineering resources.
Download this joint guide from Mode and Sisu to learn:
The key characteristics of modern data architecture
How to decide when to make improvements to your stack
How to future-proof your approach to analytics as your data team grows