"When working with Google BigQuery, even the minimum computer power is enough to process any amount of data. Since the calculation takes place on Google servers, your device will not participate in processing; you only leave a request and collect the results. Everything happens faster, easier, more efficiently."
Dmitry OsiyukLead Analyst MacPaw.
How did BigQuery help MacPaw take data management to the next level?
About the client:MacPaw is a Ukrainian IT product company that develops and promotes programs for macOS and iOS. Alexander Kosovan founded the company in 2008. MacPaw comes from Ukraine, so the support and development of Ukraine is an essential part of the company’s culture.
MacPaw products include CleanMyMac X, Setapp, The Unarchiver, and others. More than 30 million people use MacPaw software today. MacPaw applications are installed on one in five Macs in the world.
Project Start Date: May 30, 2020.
Project End Date: Collaboration Continues
Challenge: MacPaw works with large amounts of data. Data processing is one of the regular tasks of business analysts, often requiring a significant investment of time and resources. The company began looking for the best solution to speed up work with information. MacPaw was unwilling to buy additional servers as the most obvious alternative because:
Their idle time is longer than the duration of the actual load;
They need extra protection.
Solution: The company chose BigQuery from Google Cloud. The MacPaw team uses it as a base for data storage and processing, taking the power of Google’s servers “for rent” without purchasing their servers. Based on BigQuery, MacPaw created an internal product – Data Hub. In it, the team collected an Infobase from MacPaw sites and other systems, actively using it for analytics and reporting.
Why did MacPaw choose BigQuery?
BigQuery allows you to calculate data quickly.
BigQuery is secure enough to store any Business Critical Data in it.
Payment for product services depends on the amount of processed data, which is convenient for large and small businesses. Therefore, if a company does not need to work with terabytes of information, BigQuery saves costs significantly.
BigQuery has a user-friendly and simple interface. It facilitates the work of analysts because it does not require the use of programming languages.
It offers a BigQuery ML solution that allows you to use the power of Google Cloud for machine learning and artificial intelligence for data processing.
Suitable for companies using other Google products (Google Analytics, Google Sheets, etc.).
BigQuery also easily integrates with Facebook or Backend CRMs HelpDesk data and visualizes it using Google Data Studio.
Results: MacPaw considers the main business benefit — the increased productivity and efficiency of teams working with large amounts of data. BigQuery saves time waiting for calculations and results processing. It increases the productivity of business intelligence and the company’s speed as a whole.
The product is easily scalable and flexible in management, making it easier for data engineers to integrate and allow more data to be hosted. In addition, working with BigQuery enables you to save money on purchasing external servers.
"When working with Google BigQuery, even the minimum computer power is enough to process any amount of data. Since the calculation takes place on Google servers, your device will not participate in processing; you only leave a request and collect the results. Everything happens faster, easier, more efficiently." Dmitry Osiyuk, Lead Analyst MacPaw.
Cloudfresh Role: As a Google Cloud Premier Partner, Cloudfresh provided full consultation to MacPaw on working with BigQuery and helped integrate the product into the company’s ecosystem.
While Google has detailed white papers where you can find a solution to almost any problem, the MacPaw team has turned to Cloudfresh for some critical strategic and technical issues. In all cases, Cloudfresh support was lightning fast. Therefore, Cloudfresh continues to help MacPaw with the backing in case of software issues and cloud ecosystems development.
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