June 2022 Summaries

The Census team is hosting Summer Community Days, a 2-day event for data professionals to connect and celebrate the summer season. The event will feature virtual workshops and in-person happy hours in select US cities.

dbt is a modern data stack tool that helps create cookbooks, or data models, using SQL. These models are used to standardize core KPIs across business teams and ensure accurate data representation. dbt allows for faster run times, eliminates the need for trial and error, and increases transparency into available data. It also enables self-service data culture by making it easy to access and understand data definitions and explanations. The tool is widely used in the analytics engineering community and has a small learning curve due to its reliance on SQL skills. By using dbt, business users and data analysts benefit from faster and more accurate data models, which ultimately lead to better decision-making and increased business impact.

Census has partnered with Help Scout to enable customer success teams to deliver help with a personal touch, combining email, live chat, and a knowledge base for better customer experiences. The partnership allows users to self-serve with data in the warehouse, powering operational use cases such as calculating account health scores, improving visibility and productivity, and prioritizing tickets. With Census, customers can centralize their data and sync it to Help Scout in minutes, without relying on engineering favors. Additionally, Help Scout's Revenue Operations team uses Census internally to sync customer data with business tools like Salesforce and HubSpot, enriching accounts with product usage context and tracking onboarding funnel metrics.

The Operator`, the new blog of Census, is now live, offering a single source of truth about customers for all teams to benefit from. It aims to democratize access to data knowledge and empower data folks with accessibility to get the information they need when they need it. The blog has been revamped with new features and functionality, including a dynamic table of contents, content search by keyword, faceted search and filtering, and an author index. These changes aim to make Operational Analytics more accessible and user-friendly for everyone.

Today, we’re excited to announce support for Azure Synapse, Microsoft’s cloud data platform, as a source for Census reverse ETL. We’re also releasing an integration with Microsoft Dynamics 365 as a destination, so customers can sync their source of truth to their CRM to deliver more engaging customer experiences. With the integration with Azure Synapse, data and operations teams can power use cases such as creating 360º Customer Profiles, Lead and Account Scoring, and Personalized Campaigns by syncing all modeled data in the warehouse into any business application. Similarly, with the integration with Dynamics 365, customers can self-serve with data in the warehouse and automate workflows including identifying Upsell Opportunities, Lead Scoring and Routing, and Real-Time Alerts. Census also supports syncing data and dynamic audience segments into Microsoft’s ads platforms, allowing users to leverage the Microsoft ecosystem for more effective marketing and advertising efforts.

There’s a certain sense of security that comes from working with numbers, but in reality, the world doesn’t have the attention span for stability and certainty. Businesses need to learn to embrace uncertainty by managing risk and preparing for unknown outcomes. This preparation propels them forward in the long run. Data can create an illusion of certainty where none exists, and precision can become a prison as quickly as a protector. Instead, businesses should focus on telling broad stories that are likely to be correct rather than narrowing down to pet theories. A data team's prime directive is to accurately depict reality, but they also need to recognize the limitations of their analysis and acknowledge uncertainty. By doing so, they can rescue executives from always having to be right and precise, allowing for a deeper understanding of the business and its place in the world.

The Census Services Partner Program aims to foster data transformation initiatives with Census by providing consulting services, training, and co-marketing activities. The program is designed to help organizations get the most out of Census by offering product knowledge excellence, educating the market together, and co-selling and co-delivering customer success. The program is open to agencies, systems integrators, and consultancies that want to grow their business with Census and unlock access to go-to-market resources and recognition from customers.

Snowflake is enhancing its cloud data warehouse capabilities with External Functions and Stream Triggers to enable more efficient and cost-effective reverse ETL pipelines. This allows customers to orchestrate their workflows and personalize customer experiences without incurring unnecessary costs or credits. By leveraging Snowflake's Stream Triggers, customers can save time and credits when extracting data from their warehouses, especially for low-latency use cases and spiky workloads that require frequent updates. Additionally, Snowflake's external functions provide a more efficient alternative to traditional orchestration methods, with estimates suggesting a cost savings of 10-100x compared to traditional polling approaches.

The Census community team is launching Summer Community Days, a 2-day practitioner-first event on July 28-29, designed to support data practitioners in learning from each other and sharing expertise. The event will feature virtual programming and in-person happy hours in select US cities, covering technical deep dives and business-driven sessions to help attendees build their skills and network with peers. A call for proposals is also open for 30-minute presentations on various topics related to data management and leadership, with a deadline of June 30 at 11:59 pm PT. The event aims to provide a platform for data practitioners to learn from each other, share knowledge, and stand out in their careers.

Planning is a crucial aspect of any organization, and it's not about having a perfect plan but rather the process of planning itself that brings value. While it's impossible to predict every obstacle or outcome, planning helps teams imagine scenarios, prioritize resources, and make informed decisions. The act of planning is beneficial in itself, even if the final plan doesn't come to fruition as expected. By making a plan, organizations can uncover milestones, identify potential obstacles, and create fallbacks for unexpected events. This process also enables prioritization, sets clear goals, and facilitates documentation, which is essential for smooth handoffs and knowledge transfer. Ultimately, planning is a living thing that grows and changes as new information becomes available, and its value lies in the process itself rather than the final plan.

The value of data lies not in its quantity but in its usefulness, and context is crucial to understanding its significance. Data teams must add context to their findings to provide actionable insights that influence business decisions. Context refers to the network of connections among data points, which affects how data is collected, defined, and used. A strong data analyst adds context to reports, enabling them to look forward rather than just backward. The "what," "why," and "how" are essential in answering questions, and understanding these parameters helps build an infrastructure that evolves with changing metrics and KPIs. Contextualizing data aligns teams by providing a shared frame of reference, making it easier for product and development teams to understand the impact of data-driven insights, ultimately driving strategic decisions earlier.

The shift from DIY solutions to dedicated tooling is crucial for startups and growing businesses as it leads to efficiency, cost-effectiveness, and improved business operations. Implementing a modern data stack allows companies to focus on their core job: drawing insights from the data and using those insights to improve their business. This approach enables analysts and engineers to concentrate on quality analysis rather than patching together makeshift solutions. By outgrowing DIY data stacks, businesses can properly scale with growth, reduce errors, and increase trust in their data infrastructure. Investing in a modern data stack is not an expense, but rather a reallocation of resources that leads to better business outcomes.