Once you’ve structured your data stack and optimized your costs, it’s time to think about generating business value. Let’s look at a few examples of that below. You can also offset data costs by saving money in other areas of your business or by finding opportunities to monetize your data. Use your cloud data warehouse’s built-in resource monitors Use metadata to get visibility over your cloud data usage Here are three ways to reduce your data spend while you work toward generating business value from your data: Self-service analytics, so you don’t create bottlenecks for your data teamĪs a startup, we’re guessing cost may be an issue. Scriptable, so you can easily manage and document changes, reuse solutions, collaborate, and automate Scalable, cloud-native, and flexible, so they can accommodate your changing needsĮfficient and lean, so you don’t add unneeded complexity as you scale In general, startups should look for tools that are: Data experience tools for startups: ThoughtSpot, Looker Data transformation options for startups: dbtĭata experience and analytics tools that make it easy for business users to visualize, interact with, and derive insights from your data. Cloud data warehouse options for startups: Snowflake, Databricksĭata transformation tools that prepare your data inside your cloud data warehouse to make it easier to analyze. ETL options for startups: Fivetran, MatillionĪ reliable cloud data warehouse to store and manage huge volumes of data and scale storage as needed. What you need in your startup data toolkitĮxtract, transform, and load tools ( ETL ) to pull data from your sources and prepare them for your cloud data warehouse in an organized, intuitive manner. You need a modern data stack: a collection of tools and cloud data technologies to take you from data sources to data insights as efficiently as possible. If you don’t create a scalable, flexible, and governable data stack, you’ll struggle to derive any value from your data-let alone use it down the line to create new revenue streams. Step 2: Build a modern data stack that can scale with you Ask questions to find out why you’re collecting this data and where it’s going. Audit your business processes and inventory the data you’re accumulating. You need to understand your data, where it’s coming from, and how you’re collecting it. How to structure your startup’s data for more value Step 1: Identify your sources of data Once you have a strong grasp on the questions above, you can take action by building a reliable data infrastructure. How should we prioritize our analytics capabilities? Does our leadership recognize analytics as a revenue driver? If not, you might want to take a look at this guide on assessing the ROI of improved analytics. Think about what functions or insights your customers most often demand and how you can put them in the driver’s seat. How important is self-service analytics for our customers? If you’re not prioritizing self-service analytics for your end users, you might be missing out on a huge opportunity. If you can identify the commercial value of your data, you’re already a huge step ahead. What is our data worth? Frankly, there’s a very good chance that your company’s data is currently worth more than your company. Use these to guide your thinking when it comes time to make decisions. So how can you go from sitting on a slush pile of valuable data to turning it into dollars and business value? A few questions to guide your data strategyīefore you turn your startup data into revenue, it’s best to begin with some fundamental questions. You aren’t bogged down with “how we’ve always done things.” You have the chance to come out of the gate swinging. You aren’t stuck with legacy systems or a data-resistant culture. In fact, two-thirds of executives aren’t confident about their ability to access or use data with their existing tools and resources.Īnd here’s where your business has the advantage. In fact, it could become your biggest competitive advantage.Īfter all, the market incumbents-all those competitors with bigger pockets and brands-haven’t actually figured out how to use their data properly yet. All that user data and lead data and customer data and people data and third-party data and…and…and…īut when it comes down to it, your startup data doesn’t have to be a burden. And we bet that the growing mountain of data you’re generating feels like one more area of your business that needs to be optimized, organized, and sorted out.
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