Directives and Pipes in Angular/

Create Your First Data Pipeline with a Dashboard

Create Your First Data Pipeline with a Dashboard

According to the Statista 2022 analysis, the quantity of data generated, recorded, replicated, and consumed globally is predicted to skyrocket to 181 zettabytes from 2021 to 2025:

The volume of data generated, recorded, replicated, and consumed globally in zettabytes (2010-2025)

Data is meaningless without professionals who convert it into valuable insights. Here are a few examples of how a data scientist offers value to a company:

  • They allow a business to make better decisions based on the insights.
  • They suggest actionable goals based on trends that will help the company flourish.
  • They determine new opportunities and make judgments based on measurable, data-driven evidence, and evaluate these conclusions using consumer insights.
  • They perform target audience identification and refinement based on buyer trends.

As a result, modern organizations are awash in data which necessarily involves data processing and analysis. In this project, we’ll learn to create a data pipeline and interactive data visualization in Python using Kedro and hvPlot to get valuable insights from our data.

  • Kedro is an open-source Python framework for creating systematic, reusable, and modular data pipelines.
  • hvPlot is a high-level plotting API based on HoloViews. It offers an alternative to the static plotting API offered by Matplotlib and other libraries. It provides numerous interactive features such as panning, zooming, hovering, clickable/selectable axis, legends, and so on.

We will begin by building a data pipeline from scratch with Kedro. We’ll introduce data preprocessing in our data pipeline along the way and run our data pipeline successfully. We’ll get an overview of the static and interactive plots with Pandas and hvPlot, respectively. Then, we’ll transform the processed data further and display our findings as interactive plots.