Join our Smart Analytics with Big Query and Looker Webinar
Click the link to join
About the Event
01:45 pm: Registration and welcome
02:00 pm: Introduction & Welcome Speech
02:10 pm: Data Warehouse Modernization with Big Query & Smart Analytics with Looker
- The business problem
- Google BigQuery and Looker: A match made in the cloud
- Modern Workflows work better with BigQuery and Looker
- Case Study: Continuous Intelligence Ecosystem with BigQuery and Looker
02:25 pm: Bridging the technical gap between data and users with Looker
- A Looker Walkthrough (demo)
02:50 pm: Q&A
Join us for our dbt meetups
Register for our live event
We are excited to help bring HCM-based folks and folks in the surrounding areas from the dbt Community together! Looking forward to socializing and meeting in the first HCM-dbt-meet up.
Expect a happy hour, some bites, refreshments, and good vibes.
🗣️Presentation #1: Working with dbt, getting started as an Analytics Engineer
Speaker – Hoang Tran, Lead AE, Joon Solutions
🗣️Presentation #2: Making sense of the modern data landscape
Speaker – Huy Nguyen, CTO & Co-founder, Holistics (Forbes Asia 30 Under 30)
➡️ Join the dbt Slack community: https://www.getdbt.com/community/
📣For the best Meetup experience, make sure to join the #local-vietnam channel in dbt Slack (https://slack.getdbt.com/)
We offer services for the modern data stack. Our experts will deploy modern data solutions at blazing speed. Our team delivers results 30x faster and at 1/2 the cost of one data engineer. All of our services are developed as business first, and focus on success criteria. We enable non-technical users to explore and share information that matters. Radically change the way your organization understands data.
Our approach to modern data projects
Data should be simple
Let us help!
Our use case backlog approach.
A use case is a logical grouping of:
- Upstream data pipelines
- Datasets and procedures
- Downstream pipelines, reports, dashboards and business apps
With the objective to:
- Recommend a product based on market trends and user purchase behavior
- Report profit and losses
- Track product sales volumes
We follow this methodology of business case first with all of our projects. Together we develop a list of priorities that are important to your organization and create a shared backlog to work on together. Through this process we offer a transference of knowledge and understanding throughout all of our projects. We aim to solve real business issues important to stakeholders and deploy a data driven culture above all else.
How do I get started?
Everything starts with success
Everything starts with defining success criteria. First we meet with your team and project stakeholders to define success for your organization. All of our engineers are certified experts from our technology vendors and have experience working with companies that are similar to yours. We will send you an architecture review, scope of work and our recommendations on how best to accomplish your company’s goals. Whether that be one of our sprint packages or ad hoc support.
Once we have defined what success looks like, we develop a use case backlog and get to work! We provide you with a Slack Channel and a Trello board to optimize communication and support.
Throughout the project we will update you on hours used and if you are nearing your minimum commitment. If you feel you need more, simply let the team know and we will provide you with additional support at the same flat rate with no additional charge.
Our sprint packages are done in 8 to 12 week sprints and follow guidelines set by our technology partners. We create a scope of work that we create as a team and we always stick to best practices. We make sure everything follows the business use case and success criterial that we predefine together. We also offer continued support packages for all of our projects.
Analytics Engineers, Data Scientists, Data Engineers, Data Analysts, Data Architects. There are so many different people needed to make a project a success. Luckily we have them all on staff and ready to work on your project. Whatever your project needs we manage the allocation of engineers on the backend. Offering you a flat rate for all Joon Engineers.
Want to learn more about data? Check out our blog, Refined and Refactored
BI tools choice and its impact on model planning
Exploratory Data Analysis (EDA) using SQL and Datagrip
How to make basic API requests with Postman
Interested in working with the Joon Team? Read our case studies and see what our customers have to say
Our Favorite Data Stack
Freebies and Special Offers
Together with our favorite technology partners,
we’ve put together special offers including free trials,
sponsored POC’s, and discounted product offerings.
Click on their logo to learn about our favorite
data stack and exclusive offers available
to Joon Solutions customers
Why the modern data stack?
Cloud Based Data Democratization
The modern data stack is the latest wave in data utilization. As more and more companies move to SaaS based software and cloud driven technology the MDS is the quickest and easiest way to put data in the hands of the people that need it. For years people have been dealing with backward facing reporting and analytics, taking weeks or months to get valuable insights. With MDS data is assessable to all and far easier to scale.
A modern data stack will radically decrease report generation time and ensure up-to-date reports. One of our customers recently went from data availability of 8 hours to less than 10 minutes. We streamlined reporting after replacing manual processes and an on-prem databases with a modern data stack, we were able to generate monthly reports in days instead of weeks.
A modern data stack allows your data team to be more productive by increasing available data without consuming in-house IT or DevOps resources. It was developed with ease of use in mind. Before implementing an MDS, businesses relied on manual IT intensive processes and data teams could only carry out their functions after the DevOPs team provided propre access to data streams.
A modern data stack will improve data reliability and eliminate the burden of maintenance. Automated data tools detect and respond to schema and API changes without human intervention, so data teams don’t have to worry about pipeline failures, resource availability or data gaps.
Intuitive and easy to use, modern BI tools are designed to make data accessible to business users and technical employees alike. Before implementing a modern data stack, only relatively small operational teams routinely consulted analytics. Adopting a modern data stack creates an increased number of active users and a typical increase of analytics dashboards by 10x company wide.