Have you ever had to analyze big data sets for your business? Was it a challenge for you? As the levels of information we collect tend to increase, we may find limitations in processing and analyzing data from a classic spreadsheet (eg: backend errors, latency issues). In these instances, you may want to consider using a different set of tools that go beyond spreadsheets and use the power of the Cloud. In this episode, James and Jenny explain us how BigQuery provides us with a powerful processing power to quickly analyze big chunks of data sets in a few seconds.
To use BigQuery, you need first to have a Google Cloud Platform (GCP) account set up, where you will store your data sets. If you don?t have an account, you can sign up at cloud.google.com/bigquery: click ?try now? and sign in using any existing Gmail or Google account information. GCP uses a pay-as-you-go model, so you will pay according to how much data you need to store in the Cloud. The good news is that you will be offered a free storage quota, and may be able to get all the insights you need while still remaining under the free limit.
Once your account is setup, you?ll be prompted to create data tables and run as many queries as you want in the BigQuery interface (at bigquery.cloud.google.com). To run queries and work with BigQuery, you will need to have basic knowledge of SQL, which is the structured query language. But if you don?t have SQL knowledge, don?t worry: there are a few options you can consider. First, you can learn the basics of SQL by taking advantage of the resources widely available online (check out this video https://goo.gl/9HEul6). Otherwise you can consider using some third party tools that will help you with data visualization without SQL. James walks us through some examples of tools available online.
For this episode, Jenny and James show us a use case where BigQuery proved to be just the right solution to a retail business. They used the example of a souvenir store that needs to know the list of the most popular US names to craft customized named items. Jenny shows us how she got this list by using BigQuery and the public dataset available online. Public datasets are great resources that you can play with if you want to try BigQuery and don?t have any existing bigdata available : you?ll find them at https://goo.gl/UgRzb2. In a fraction of seconds, Jenny was able to get the top 50 most used US names, out of the analysis of 5,552,452 rows!
If you want to learn more about the power of BigQuery, you can take advantage of different guides available online, at https://goo.gl/0KasNU. If you have limited knowledge on this topic, we recommend that you get started with the ?Quickstarts? and ?Concepts? rubrics for a great overview of the basics.
This was our second episode on the Cloud (check out our first episode at https://goo.gl/jI5HMa) Feel free to let us know your thoughts and questions in the comments section below!
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Analyze big data by using BigQuery | Google Cloud Platform | The Apps Show