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Aravo Solutions > Case Studies > Grammarly Enhances Communication with Databricks Lakehouse Platform
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Grammarly Enhances Communication with Databricks Lakehouse Platform

Technology Category
  • Analytics & Modeling - Machine Learning
  • Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
  • Construction & Infrastructure
  • Education
Applicable Functions
  • Sales & Marketing
  • Warehouse & Inventory Management
Use Cases
  • Construction Management
  • Perimeter Security & Access Control
Services
  • Data Science Services
  • System Integration
The Challenge
Grammarly, a company that provides AI-powered communication assistance, was facing challenges with its legacy, homegrown analytics system. As the company grew, it became increasingly difficult to evaluate large data sets quickly and cost-effectively. The existing system was time-intensive to learn, making it challenging to onboard new hires. It also failed to meet the needs of essential business functions, particularly marketing, sales, and customer success. Analysts often had to resort to copying and pasting data from spreadsheets as the system couldn't effectively ingest the external data needed to answer critical business questions. Reporting was also a challenge as the system didn't support Tableau dashboards. Furthermore, Grammarly sought to unify its data warehouses to scale and improve data storage and query capabilities. The existing setup, with large Amazon EMR clusters running 24/7, was driving up costs. Data silos emerged as different business areas implemented analytics tools individually, and a single streaming workflow made collaboration among teams challenging.
About The Customer
Grammarly is a technology company that aims to improve lives by enhancing communication. Its AI-powered communication assistance provides real-time suggestions to help individuals and teams write more confidently and achieve better results. Grammarly offers a range of products including Grammarly Premium, Grammarly Business, Grammarly for Education, and Grammarly for Developers. These offerings deliver leading communication support wherever writing happens. The company serves 30 million people and 50,000 teams worldwide, helping them write more effectively every day. As the company grew, it faced challenges with its legacy analytics system, which made it difficult to evaluate large data sets quickly and cost-effectively.
The Solution
Grammarly decided to migrate from its in-house built solution to the Databricks Lakehouse Platform. This platform was chosen over other vendors like Snowflake due to its support for data science and machine learning capabilities, predictable costs with growing scale, and the ability to maintain complete control and ownership over its own data. The lakehouse architecture provided a consolidated interface for analytics, leading to a single source of truth and confidence in the accuracy and availability of all data. Teams across the organization could use Databricks SQL to conduct queries within the platform on both internally generated product data and external data from digital advertising platform partners. They could also easily connect to Tableau and create dashboards and visualizations. By consolidating data onto one unified platform, Grammarly eliminated data silos. To manage access control, enable end-to-end observability, and monitor data quality, Grammarly relied on the data lineage capabilities within Unity Catalog.
Operational Impact
  • With the Databricks Lakehouse Platform, Grammarly's engineering teams now have a tailored, centralized platform and a consistent data source across the company. This has resulted in greater speed and efficiency and reduced costs. The lakehouse architecture has enabled low-latency data aggregation and query optimization, allowing the team to quickly receive feedback about new features and understand if they are being adopted as expected. It has also helped them understand how groups of users engage with the UX, improving the experience and ensuring features and product releases bring the most value to users. The migration to the lakehouse architecture also solved the challenge of access control over distributed file systems, while Unity Catalog enabled fine-grained, role-based access controls and real-time data lineage. This has helped Grammarly foster a data-driven culture where employees get fast access to analytics without having to write complex queries, all while maintaining Grammarly’s enterprise-grade security practices.
Quantitative Benefit
  • 110% faster querying, at 10% of the cost to ingest, than a data warehouse
  • 5 billion daily events available for analytics in under 15 minutes, down from 4 hours
  • Elimination of data silos, leading to more efficient data management and analysis

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