Wanda  Huel

Wanda Huel

1600480800

Hands-On Tutorial On Holoviews – Automated Visualization Based On Short Data Annotations

Data Visualization is a scientific study of the data in order to find out the anomalies, patterns, or trends in a particular dataset. It can be done using a variety of plots and graphs which we can use to visualize different properties of the attributes of the dataset. Visualization is one of the easiest ways of understanding the data as we can clearly visualize the data with our naked eyes and our brain processes the data to give us a clear picture of what the data is trying to say.

Visualization can be of many types like Bar Charts, Histograms, Scatter Plots, etc. which can be used on different types of data to gain useful insights about the data. Python has a large number of libraries/modules which can be used for data visualization and creating highly informative and attractive graphs and plots. Holoviews is one such library that makes the process of visualization easier such that we can create highly informative and insightful visualizations in a few lines of code.

Holoviews is an open-source python library that makes data visualization easier. Holoviews works on conveying the message that data is trying to tell rather than focusing on how to plot visualizations. Holoviews works on Numpy and Params, and for visualization, it supports ‘Bokeh’ and ‘Matplotlib’.


In this article, we will see how we can create different types of visualizations using Holoviews and how we can manipulate them according to our requirements.


#developers corner #data visualization #python

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Hands-On Tutorial On Holoviews – Automated Visualization Based On Short Data Annotations
 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

Sid  Schuppe

Sid Schuppe

1617988080

How To Blend Data in Google Data Studio For Better Data Analysis

Using data to inform decisions is essential to product management, or anything really. And thankfully, we aren’t short of it. Any online application generates an abundance of data and it’s up to us to collect it and then make sense of it.

Google Data Studio helps us understand the meaning behind data, enabling us to build beautiful visualizations and dashboards that transform data into stories. If it wasn’t already, data literacy is as much a fundamental skill as learning to read or write. Or it certainly will be.

Nothing is more powerful than data democracy, where anyone in your organization can regularly make decisions informed with data. As part of enabling this, we need to be able to visualize data in a way that brings it to life and makes it more accessible. I’ve recently been learning how to do this and wanted to share some of the cool ways you can do this in Google Data Studio.

#google-data-studio #blending-data #dashboard #data-visualization #creating-visualizations #how-to-visualize-data #data-analysis #data-visualisation

Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management

Jeromy  Lowe

Jeromy Lowe

1599097440

Data Visualization in R with ggplot2: A Beginner Tutorial

A famous general is thought to have said, “A good sketch is better than a long speech.” That advice may have come from the battlefield, but it’s applicable in lots of other areas — including data science. “Sketching” out our data by visualizing it using ggplot2 in R is more impactful than simply describing the trends we find.

This is why we visualize data. We visualize data because it’s easier to learn from something that we can see rather than read. And thankfully for data analysts and data scientists who use R, there’s a tidyverse package called ggplot2 that makes data visualization a snap!

In this blog post, we’ll learn how to take some data and produce a visualization using R. To work through it, it’s best if you already have an understanding of R programming syntax, but you don’t need to be an expert or have any prior experience working with ggplot2

#data science tutorials #beginner #ggplot2 #r #r tutorial #r tutorials #rstats #tutorial #tutorials

Wanda  Huel

Wanda Huel

1600480800

Hands-On Tutorial On Holoviews – Automated Visualization Based On Short Data Annotations

Data Visualization is a scientific study of the data in order to find out the anomalies, patterns, or trends in a particular dataset. It can be done using a variety of plots and graphs which we can use to visualize different properties of the attributes of the dataset. Visualization is one of the easiest ways of understanding the data as we can clearly visualize the data with our naked eyes and our brain processes the data to give us a clear picture of what the data is trying to say.

Visualization can be of many types like Bar Charts, Histograms, Scatter Plots, etc. which can be used on different types of data to gain useful insights about the data. Python has a large number of libraries/modules which can be used for data visualization and creating highly informative and attractive graphs and plots. Holoviews is one such library that makes the process of visualization easier such that we can create highly informative and insightful visualizations in a few lines of code.

Holoviews is an open-source python library that makes data visualization easier. Holoviews works on conveying the message that data is trying to tell rather than focusing on how to plot visualizations. Holoviews works on Numpy and Params, and for visualization, it supports ‘Bokeh’ and ‘Matplotlib’.


In this article, we will see how we can create different types of visualizations using Holoviews and how we can manipulate them according to our requirements.


#developers corner #data visualization #python