June 2022 Summaries

Fivetran has been recognized as the Partner of the Year by Google Cloud, Snowflake and Databricks for its exceptional cloud data integration technology. The company's focus on collaboration and customer-centricity has led to successful partnerships with these leading data destination providers. Fivetran powers reliable data movement from hundreds of sources into platforms like BigQuery, Snowflake and Databricks, helping joint customers realize successful data projects that deliver more impactful business value faster.

Fivetran is celebrating Pride Month with various initiatives to support the company's diverse workforce, including revamping its existing employee resource group into a global community called Fivetran PRIDE. The company has hosted virtual drag bingo and discussion panels led by thought leaders from the LBGTQIA+ community. Fivetran is committed to creating an inclusive environment for all employees beyond Pride Month, with ongoing educational programming on topics such as gender inclusivity, allyship, and mental health.

Fivetran Transformations for dbt Core helps data analysts optimize their daily processes and save time on manual tasks. By using pre-built SQL models, reducing data latency through synchronized ELT, and increasing observability with ELT data lineage graphs, analysts can focus more on uncovering insights and less on writing SQL schemas or dealing with data pipeline issues. This solution is free to use and can save money while improving efficiency and trust in the data.

Julie Richardson has joined Fivetran's Board of Directors as an independent board member and member of the company's audit committee. She brings 25 years of Wall Street experience to her new role, having previously worked at firms like Merrill Lynch and J.P. Morgan before transitioning into private equity. Richardson is excited about Fivetran's commitment to diversity, equity, and inclusion (DEI) and its mission to address the significant market need for data accessibility across various applications and databases. She appreciates the founders' enthusiasm and their willingness to learn, as well as the company's culture of teamwork and perseverance.

Data residency is a growing concern for businesses as data flows globally from distributed teams, and various sources are stored in different cloud data destinations. Compliance regulations such as GDPR, India's Personal Data Protection Bill, and the California Consumer Privacy Act require companies to protect user data by ensuring that citizen or resident data is only collected, stored, and processed within the country of residence. While data residency, data sovereignty, and data localization are often used interchangeably, they have nuances and specifics that should be understood when building a data compliance strategy. As companies move to the cloud, it's crucial for organizations to incorporate the demands of this fast-evolving privacy landscape into their business strategies. Key considerations in establishing data residency requirements include understanding where data originates from, controlling its storage location, and adhering to global or industry policies.

Data integration is crucial for businesses aiming to master data and analytics. A hierarchical model, similar to Maslow's hierarchy of needs, outlines the progression from raw data collection at the bottom to artificial intelligence and machine learning at the top. The foundation of this model includes data extraction, loading, modeling, transformation, visualization, decision support, business process automation, and AI/ML. Many organizations struggle with prematurely hiring data professionals before establishing a strong foundation in data collection and management. A modern data stack is essential for building this foundation, consisting of a data pipeline, destination (data warehouse), transformation tool, and business intelligence platform. As the organization grows, it's important to promote data literacy across all levels and build robust data architecture to support increased operational use of data. AI/ML implementation depends on capabilities like a modern data stack, mature analytics operations, and infrastructure to support data scientists.

Fivetran has introduced a new feature, history mode, which enables users to implement Type 2 slowly changing dimensions (SCD) in their historical database analytics without any coding. This feature is currently available for DynamoDB, MariaDB, MongoDB, MySQL, Oracle, PostgreSQL, and SQL Server. History mode creates a record of every change in the database transaction logs and appends those records to specified tables, allowing users to track changes made to their data over time. This feature is particularly useful for customer journey analytics, order funnel analytics, and other historical tracking use cases on databases. Users can enable history mode through Fivetran's UI by hovering over the table and selecting "history mode" within the dropdown menu.

The Great Resignation has prompted a massive number of employees to quit their jobs, leading to an urgent need for employers to retain key talent. People analytics can help organizations understand employee pain points and take steps to retain top talent. HR data analytics can provide valuable insights into employee compensation, benefits, and rewards, as well as evaluate diversity and inclusion efforts. By using relationship mapping and predicting which employees are likely to leave, companies can foster meaningful relationships with their workers and increase employee engagement. Building a modern data stack is crucial for integrating various data sources available to organizations.

Amidst economic uncertainty, the demand for accurate and up-to-date data is increasing as businesses seek to become more agile, efficient, and resilient. Fivetran, a cloud ELT data provider, has doubled its revenue since its last fundraise seven months ago and anticipates further growth in the coming year due to increased reliance on data-driven insights for weathering difficult market conditions. Businesses are leveraging modern data infrastructure to maximize efficiency, identify opportunities, and increase business agility. Despite fluctuating tech valuations, Fivetran's cloud data infrastructure market continues to grow rapidly, making it an ideal time for businesses to partner with them or join their team.

Thrive+, a new employee resource group (ERG) at Fivetran, aims to create a safe and supportive space for both neurodiverse and neurotypical individuals within the company. The ERG was founded by Nora Gentry, who has also shared her personal journey of giving up alcohol and maintaining mental health in the tech industry. Thrive+ focuses on empowering members through information, resources, and awareness, emphasizing that mental health matters at Fivetran.

Fivetran has introduced a new App Reporting data model that simplifies the process of integrating Apple App Store and Google Play data into a unified schema for seamless reporting. This feature is particularly useful for app platform source data, which often requires extensive knowledge about the data before transformation across sources. The App Reporting data models allow aggregation and modeling of data using Fivetran's pre-built connectors for Google Play and Apple App Store. Users can standardize schemas from various app platform connectors and create reporting models for all activity aggregated daily and by app along dimensions such as country, OS version, app version, traffic source, and device. Additionally, the data model includes a data dictionary and model lineage graph for customer references. Fivetran Transformations for dbt Core can be leveraged to centralize end-to-end managed ELT pipelines into one platform. Integrated scheduling ensures that app reporting data models only run upon completion of connector syncs, ensuring accurate generation with the most up-to-date data.