CrunchBase provides data about mergers and acquisitions of companies/firms in the data and analytics space. CrunchBase data can be very useful when building a list of Leads for Business to Business (B2B) Marketing to target specific companies while looking out for similar companies in that niche. It can also come in handy during explorative analysis. Although CrunchBase does the work when used independently, it is highly recommended to use it with Snowflake.
Snowflake serves as a Cloud-based Data Warehouse with Modern Cloud Technologies for the analysis and visualization of data. CrunchBase Snowflake Integration allows you to analyze your CrunchBase data and fetch meaningful insights.
But the questions arise: Can you transfer CrunchBase data to Snowflake?
If so, how best can it serve its purpose inside a powerful Cloud-based Data Warehouse like Snowflake?
This article will introduce you to CrunchBase and will provide you with a step-by-step comprehensive guide to setting up CrunchBase Snowflake Integration. It will also provide you with how to use CrunchBase’s data to your advantage and the best use cases of CrunchBase Snowflake Integration.
What is CrunchBase?
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CrunchBase is a leading provider of private-company prospecting and researching solutions. It simply provides information about a Lead (for B2B) to the company/organization/users. These firmographics coupled with your internal data will help you make more informed/data-driven decisions and target gain points.
Crunchbase is a website that allows users to look up information about private and public companies. The portal includes real-time financing data, trend analysis, and professional biographies. To provide the most accurate and up-to-date information, the platform collects data from 200,000+ contributors, 2,000+ venture partners, and millions of data points throughout the web. Crunchbase is a global leader in providing business, investment, and industry data to millions of users.
Crunchbase has an active network of partners and community members with whom it communicates on a regular basis in order to promote engagement and provide highly tailored news and updates. Crunchbase has expanded into a generic collection of business information for the technology industry.
Key Features of Crunchbase
Crunchbase offers a plethora of tools to enhance the user experience. Crunchbase’s primary features include the following:
- Crunchbase allows users to create a personalized list of organizations to monitor and receive notifications when new information is available, such as IPO (Initial Public Offering) announcements or new partnerships.
- To provide a better user experience, Crunchbase integrates with a variety of third-party apps and services.
- Crunchbase’s search feature is flexible, allowing users to hunt for specific results rather than generic results.
- Crunchbase assists in the growth of a company’s brand. Your Crunchbase listing will appear when someone types your company’s name into Google or another search engine.
Visit this page to learn more about Crunchbase.
What is the need to use CrunchBase?
CrunchBase provides up-to-date data about private companies depending on the plan subscribed to. The Enterprise plan updates data in real-time. The data provided can be used to optimize the Lead Generation process (in terms of Sales and Marketing), help find similar companies in the same niche, and also take a targeted approach in making decisions.
Some of the best alternatives to CrunchBase are UpLead, Apollo.io, LinkedIn Sales Navigator, etc.
For more information on CrunchBase, click here.
What is Snowflake?
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Snowflake is a Cloud Data Warehouse service that is built on AWS or Azure infrastructure and provides an unlimited platform for storing and retrieving data. Snowflake’s design splits its “Compute” and “Storage” components, which scale differently and let clients utilize and pay for each separately.
Snowflake requires no hardware or software to select, install, configure, or administer, making it suitable for enterprises that do not want to devote resources to in-house server setup, maintenance, or support.
Snowflake’s sharing capabilities make it simple for businesses to exchange and protect data in real-time using any available ETL solution. Snowflake’s design enables Big Data adaptability.
What are the main characteristics of Snowflake?
Some of the advantages of employing Snowflake as a Software as a Service (SaaS) solution are as follows:
- Snowflake helps you to increase the quality and speed of your analytics by switching from nightly Batch Loads to Real-time Data Streams. You may increase the quality of analytics at your firm by providing secure, concurrent, and monitoring access to your Data Warehouse throughout your enterprise.
- Snowflake uses the Caching Paradigm to quickly provide cache results. Snowflake uses Persistent (during the session) Query results to avoid re-generation of the report when nothing has changed.
- Snowflake enables you to eliminate silos and assure enterprise-wide access to valuable insights, leading to superior data-driven decision-making. This is an important first step in improving partner relationships, optimizing pricing, lowering operational costs, increasing sales effectiveness, and other goals.
- Snowflake enables you to do more in-depth analyses of customer behavior and product usage. You may also leverage the whole range of data to assure customer happiness, significantly improve product offerings, and drive Data Science innovation.
- Snowflake lets you construct your own Data Exchange, allowing you to securely transmit live, regulated data. It also pushes you to strengthen data linkages throughout your business divisions, as well as with partners and customers.
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Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different Business Intelligence (BI) tools as well.
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- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
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- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
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CrunchBase Snowflake Integration
Now that you have a basic grasp of both technologies let’s try to understand the procedure to set up Crunchbase Snowflake Integration. Below are the prerequisites & the Use Cases for Crunchbase Snowflake Integration followed by a step-by-step guide to set up Crunchbase Snowflake Integration.
Prerequisites
Listed below are the prerequisites for setting up CrunchBase Snowflake Integration:
- A Snowflake account.
- A general understanding of what Snowflake is as a Data Warehouse.
Steps to Set Up CrunchBase Snowflake Integration
Listed below are the steps to set up CrunchBase Snowflake Integration:
Step 1: Log In to your Snowflake Account
Go to your Snowflake account. If you don’t have one already, click here to create a new account as shown in the image below.
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The Standard plan is just okay to handle quite a lot of things, but if you need something more dynamic, the enterprise plan allows you to dig into data as far back as 90 days and mask your data dynamically in a Multi-Cluster Warehouse.
Step 2: Find the CrunchBase Listing from the Data Marketplace
Follow the steps below to find the CrunchBase Listing from the Snowflake Data Marketplace:
- Click “Data Marketplace” from the top menu. This will redirect you to a new page.
- Under the “Categories” section on your left, click on “Business”.
- Search for “CrunchBase Enterprise: Company & Funding Data” as shown in the image below.
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Step 3: Request Access for CrunchBase Listing
After selecting “CrunchBase Enterprise: Company & Funding Data”, you will be redirected to a new page where you can find all the details of this particular listing in Snowflake Data Marketplace. Click on the “Request” button in the top right corner as shown in the image below. This will request access to the premium dataset. Once your request is approved, you’re good to go.
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That’s it. You can successfully set up CrunchBase Snowflake Integration. This gives you access to your CrunchBase data. Now, you can relate your Snowflake data to it and make Data-Driven business decisions.
Note: Another way to set up CrunchBase Snowflake Integration is using Nodejs (a JavaScript Runtime Environment). This is done programmatically and is not as straightforward as the above steps. It is a more developer-friendly approach as it uses the Snowflake SDK and CrunchBase API to perform asynchronous processes.
CrunchBase Snowflake Integration: Use Cases
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Listed below are the use cases of CrunchBase Snowflake Integration:
- Analysis of Company Firmographics: With CrunchBase data inside Snowflake, you can dig deeper into your analysis. You can go as far as finding gender-specific members of a firm.
This data query can be done with SQL which can help you track data and narrow them down to trends. The visualization tools provided by Snowflake can be used to convert the numeric output into a graphical view for better insight. - Connection of Data to Snowflake: Snowflake allows you to connect your Snowflake data and perform Explorative Analysis with the tools available all without losing on any end. With your CrunchBase data intact and your Snowflake data for references, you have a poll of data to dissect and deduce inferences from.
Conclusion
This article introduced you to CrunchBase. It provided a step-by-step comprehensive guide that you can use while setting up CrunchBase Snowflake Integration. It also provided the use cases of connecting Snowflake with CrunchBase. As shown in this article, you can connect to your CrunchBase data and load it into Snowflake for querying with your favorite tools. In summary, with SQL you can get information about moves made by Startups and Mergers.
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Share your experience of setting up CrunchBase Snowflake Integration in the comments section below!
Teniola Fatunmbi excels in freelance writing within the data industry, skillfully delivering informative and engaging content related to data science by integrating problem-solving ability.