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Achieving cloud excellence and efficiency with cloud maturity models

IBM Big Data Hub

Cloud maturity models are a useful tool for addressing these concerns, grounding organizational cloud strategy and proceeding confidently in cloud adoption with a plan. Cloud maturity models (or CMMs) are frameworks for evaluating an organization’s cloud adoption readiness on both a macro and individual service level.

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Why optimize your warehouse with a data lakehouse strategy

IBM Big Data Hub

Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. Read our blog on solving today’s challenges with a lakehouse architecture Value of data warehouse optimization Since its introduction over a century ago, the gasoline-powered engine has remained largely unchanged.

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Benefits of Using Analytics to Optimize Your Telemarketing Strategy  

Smart Data Collective

Any company that wants to implement a successful marketing strategy needs to invest in analytics technology. We have talked extensively about the importance of analytics in online marketing, but it can be just as important for traditional marketing strategies as well. Analytics is the Basis for Successful Telemarketing Strategies.

Strategy 101
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Optimizing Cost with DevOps on the Cloud

Smart Data Collective

Are you looking for a way to reduce the cost of your development efforts? The cost savings associated with DevOps on the cloud are significant. By leveraging existing cloud-based services, businesses can save time and money by avoiding costly IT overhead costs like maintenance, licensing fees, and server infrastructure setup.

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LLMOps for Your Data: Best Practices to Ensure Safety, Quality, and Cost

Speaker: Shreya Rajpal, Co-Founder and CEO at Guardrails AI & Travis Addair, Co-Founder and CTO at Predibase

Large Language Models (LLMs) such as ChatGPT offer unprecedented potential for complex enterprise applications. However, productionizing LLMs comes with a unique set of challenges such as model brittleness, total cost of ownership, data governance and privacy, and the need for consistent, accurate outputs.

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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. Unfortunately, the road to data strategy success is fraught with challenges, so CIOs and other technology leaders need to plan and execute carefully. Here are some data strategy mistakes IT leaders would be wise to avoid.

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How to build a successful AI strategy

IBM Big Data Hub

Without an AI strategy, organizations risk missing out on the benefits AI can offer. An AI strategy helps organizations address the complex challenges associated with AI implementation and define its objectives. What is an AI strategy? A successful AI strategy should act as a roadmap for this plan.