Starting or running a business today means one thing: the cloud. New software companies are born, live, and grow on the cloud, their cloud data teams never handling a single server. Every other type of company is quickly transforming into a data company, whether it knows it or not, and the rapidly growing volumes of information organizations deal with have to get stored someplace. That place is the cloud. The <a href="https://www.sisense.com/reports/dresner-wisdom-crowds-business-intelligence-market-study/" target="_blank" rel="noreferrer noopener">2021 Dresner Wisdom of Crowds Report</a> saw a quarter of respondents rate cloud technology as critical to their company’s mission (with only about 10% rating it not important). 


As organizations of all kinds across every industry grapple with the increasing volumes of data being generated, they all want (at least) two things from it: Number one, they want to store it someplace it can be accessed, analyzed, and manipulated easily (at a price they’re willing to pay). Number two, they want to derive actionable intelligence from it.


&#8220;Data by itself isn&#8217;t valuable,” said Scott Castle, Vice President and General Manager for Cloud Data Teams at Sisense. “Plus, it&#8217;s expensive to collect — but to a product leader, insights derived from real-world data are the gold standard for decision-making.&#8221;


It falls to cloud data teams and other stakeholders to weigh their options and pick the best products to meet these needs, often holding off on choosing a BI tool until they’ve settled on a cloud-based data warehouse, even if the platform could help them start evolving their business immediately. 
 
The right cloud-agnostic BI platform will connect seamlessly with any cloud data warehouse, infusing actionable intelligence into workflows and embedding data for customers into applications, experiences, and services. It will also scale as the company grows and adapt easily if the company decides to change cloud solutions. Truly robust cloud-native analytics platforms even empower users to write back the results of analyses into cloud-based data warehouses for use in a wide array of other functions.


&gt;&gt;&gt;Want to simplify data preparation? AI can help with that!


<a class="action-btn " href="https://www.sisense.com/whitepapers/data-deduplication-getting-smarter-with-ai/" target="_blank" rel="noopener noreferrer">Download the guide</a>


<h2 class="wp-block-heading">Solve your cloud warehouse dilemma with a cloud-native BI platform</h2>


The cloud warehouse and BI space has undergone consolidation in recent years that has changed relationships and considerations for many companies: Salesforce acquired Tableau, Looker is part of Google, and of course Microsoft offers Power BI and Azure cloud solutions. Cloud data teams looking for the best cloud-based data warehouse and BI platform — and the best deal for them both — often find themselves in a challenging position.


&#8220;Vendor lock-in is a real problem for product teams,” said Scott. “And it&#8217;s difficult to get the attention you need from multibillion-dollar cloud vendors. In order to bet my product on a vendor, I need to know that I have their attention and can get changes made without the threat of switching clouds.&#8221;


That makes a certain kind of sense. Data teams are most focused on cloud data management — where the data is going to live and how they’re going to handle it going forward. They don’t want to pick a storage solution that’s not going to play well with their core product or connect to their analytics and BI platform. So they hold off on choosing a BI tool until they’ve settled on a data warehouse. But that wastes time and can cost them money and market share in the meantime.


Cloud-native, cloud-agnostic analytics and BI platforms like Sisense square this circle by being able to play nicely with every kind of cloud-based data warehouse. Whatever point a data team is at in their cloud warehouse selection process, they can still connect to their cloud-agnostic BI tool and start manipulating data, testing out embedded visualizations, <a href="https://www.sisense.com/blog/new-age-analytics-sisense-extense-framework/" target="_blank" rel="noreferrer noopener">extending infused analytics</a> into their core workflow tools, and more. Understanding how your company’s experience of using the BI tool with the cloud data warehouse is just as important as understanding the experience of working with the warehouse itself. Working with both at the same time during the selection process can help you find the best fit.


Another benefit of cloud-agnostic platforms is that if circumstances change down the line and your company needs to move to a new cloud provider, you know your BI platform will still work and deliver a great experience for you and your customers. That might not be the case if you’re walled in with a cloud-BI provider combo.


<h2 class="wp-block-heading">Own your data, build for the future</h2>


There was a time, not terribly long ago, when video games were sold on physical media. Whatever happened to your save files, you knew you could count on your CD or cartridge to keep letting you play the game — it was yours. This is another important consideration when picking an analytics platform for your cloud data. 


Some BI platforms give you the ability to pipe your company’s data directly into their system, where you can manipulate and analyze it, and then do what you will with the results. This might seem like a way to save steps and money instead of choosing a cloud data platform and storing everything there, but it leaves you handcuffed to the BI solution and robs you of the ability to do more with your data down the line.


It’s important to find a cloud warehouse where you can store your data to power internal analytics and embedded applications, perform complex processes on it (like machine learning with AWS products), and use those results to power additional analytics use cases and the future of your business.


<a href="https://www.sisense.com/blog/how-skullcandy-uses-predictive-and-sentiment-analysis-to-understand-customers/" target="_blank" rel="noreferrer noopener">Sisense customer Skullcandy</a> is a perfect example of how huge the possibilities are when you pair the right cloud-based data warehouse with the right set of BI tools: To reduce return rates and improve products, Skullcandy uses a complex data science workflow. Cloud data is stored on AWS servers, where Amazon Comprehend can gather sentiment information. After using the Python language on other data to glean additional natural language processing-based insights, Skullcandy combines all these robust results within Sisense to understand what customers are saying about its products and how they feel when things need to be fixed. 


“Where in the past we had to wade through disparate, siloed data, now we can correlate a stream of negative sentiment to reviews that mention a defect,” said Skullcandy CIO Mark Hopkins. “By connecting those negative reviews on a product to the same product’s warranty claims, incoming products with similar design and engineering could be given extra attention by our product designers and engineers before going to market. And we could easily visualize how a fix could impact our warranty claim forecast. Full circle data experience: achieved.”


<h2 class="wp-block-heading">Take cloud data manipulation further with the right BI platform</h2>


Skullcandy demonstrates how the right cloud-based data warehouse combined with the right analytics and BI platform empowers companies to take analyses in bold new directions. And that’s just the beginning. Platforms like Sisense can even take the results of processes performed in Sisense and write them back to your cloud data warehouse to power the next phase of analysis and reveal truly game-changing actionable intelligence.


When data teams perform <a href="https://www.sisense.com/blog/deliver-intelligence-from-ad-hoc-analysis-via-your-bi-platform/" target="_blank" rel="noreferrer noopener">complex data preparations and analyses</a>, those results are useless if they don’t get into the hands of people who can benefit from them. Infusing insights into workflows via tools users are already familiar with allows even non-experts to manipulate data and make smarter decisions that can help evolve your business. 


&#8220;By putting customer insights directly into the tools my Customer Success Managers use to support our customers, we were able to reduce churn — and more importantly, improve our Net Promoter Scores — something that would not have been possible had we needed to train the whole team on a dedicated BI tool,&#8221; Scott said.


Additionally, when you use a cloud-agnostic and language-agnostic platform, even if you decide you need to change cloud providers, everything you’ve built can travel with you, and your end users (both in-house teams and external customers) continue having the same experience. Your data teams will also be able to use the languages they are most familiar with (SQL, Python, R) to manipulate your data in the ways that will yield the greatest impact and allow the code they build to travel to any new cloud provider.


<h2 class="wp-block-heading">Conclusion</h2>


Today’s world is a cloud world. Whatever your company does, it’s creating tons of data every day, and that data will live on a cloud data platform. You’re going to need an analytics and BI platform to get the most out of your data — powering actionable intelligence infused into in-house workflows and customer-facing applications, services, and experiences. 


If you’re still in the selection process for your cloud-based data warehouse, don’t waste time holding off to finalize your choice before you start weighing analytics options. A modern cloud-agnostic BI platform is ready to equip you for your company’s next evolution with insights from your cloud data that could change the way you do just about everything.


&gt;&gt;&gt;Want to simplify data preparation? AI can help with that!


<a class="action-btn " href="https://www.sisense.com/whitepapers/data-deduplication-getting-smarter-with-ai/" target="_blank" rel="noopener noreferrer">Download the guide</a>


Kyle Dempsey is the Field CTO in Sisense&#8217;s U.S. Northeast Region and Canada, where he delivers innovative solutions to Sisense users. Kyle specializes in business strategy, cloud architecture, and data science within the enterprise analytics space. Outside of the office, he is a frequent traveler who enjoys backpacking, paddleboarding, and walking his dog.

Simplify Cloud Analytics with the Right BI Platform

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