A fresh combination, BI and Metabase

2021 is already over and we are in 2022. But the need for the data has never reduced. To be very clear, we are so more dependent on Data and this trend is going to be there for a very long time.

Data has answered so many business questions in last few years and unlocked so much potentials with respect to taking business decisions.

Now almost every company is Data driven and they back their decisions based on the data points.

To take the right decision we need the right data. But its not only data but the Visualisation as well.

We cannot take the data to the Business Stakeholders and ask them to take million dollar business decisions.

We need to have a visualisation tool which should be simple enough for any no brainer to use without having to know the coding experience.

Metabase just does it right.

Introduction

Metabase is a BI tool which can help you to visualise the data and create the dashboard in few clicks without any SQL knowledge

Using Metabase we can connect to different types fo database or Data warehouse tools and can get insights of your data.

Metabase high level features

Opensource

Metabase is Opensource and it’s very easy to use and setup. Due to easy usability the Metabase is very famous among the startup companies.

drag and drop

Creating the aggregation or visualising is very simple. By just click and save you can create the dashboard and visualise the data.

No code

Metabase is fully web based where you do not require to have any prior SQL knowledge to write any complex logic. You can even join multiple datasets by click of a button.

share dashboard in slack at regular interval

Metabase supports the integration to slack out of the box. You can schedule the dashboard to send the report at a given frequency directly to your team or individuals.

Exporting data with defined schema

Once you visualise the data you can export the data and it maintains the schema in the exported file.

Single sign-on

You can connect LDAP users and use single sign-on.

Caching

Metabase now gives you the ability to automatically cache the results of queries that take a long time to run. Metabase supports caching where you can define the amount of time you want to store the data in the me

Sharing dashboards or questions

Metabase let’s administrators create public links and simple embeds to let you do just that.

Embedding Metabase in other applications

Metabase includes a powerful application embedding feature that allows you to embed your saved questions or dashboards in your own web applications. You can even pass parameters to these embeds to customise them for different users.

Officially supported databases

Source: https://www.metabase.com/docs/latest/administration-guide/01-managing-databases.html

Demo

There are multiple ways using which you can setup the Metabse locally.

We shall take the docker approach.

docker run -d -p 3000:3000 — name metabase metabase/metabase

Once the docker starts

Go to the url: http://localhost:3000

Setup the account.

Homepage.

Click on Ask a question.

Here you will see

  1. simple question:
  2. Custom question
  3. Native query

Simple question will help you to read and analyse the data by selecting the table name.

You can summarise on the column.

Custom question can help you where you need to apply few more custom operation on the table.

You can define the join or the aggregation column.

Define the type of chart.

You can create a dashboard and put all the question you have asked in that dashboard.

Adding the database is as simple a selecting the databse and inserting the given details.

You can define caching for the queries which takes long time to run.

You can define the duration and TTL.

Integration with Slack.

Integration with LDAP.

User management.

Adding the database.

Xray data will help you to run the profiling on top of your data.

Xray would give the count of the records and the growth of the data over the time.

It gives the dashboard to help you visualise.

Reference:

Ajith Shetty

Bigdata Engineer — Bigdata, Analytics, Cloud and Infrastructure.

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Ajith Shetty

Ajith Shetty

Bigdata Engineer — Love for BigData, Analytics, Cloud and Infrastructure. Want to talk more? Ping me in Linked In: https://www.linkedin.com/in/ajshetty28/