Biju Augustian

Biju Augustian

1575978816

Apprendre l'Unreal Engine 4 | Simpliv

Description
Durant ce cours nous aborderont le moteur dans son ensemble. En commençant par le launcher, puis les bases et les principales choses à connaitre comme le déplacement de la caméra, les options les plus courantes. Mais aussi des moyens mémo-technique pour pouvoir très facilement se retrouver dans l’interface de l’Unreal Engine, pas toujours simple quand on débute.

Nous continuerons notre découverte du moteur à travers plusieurs chapitres comprenant les différents modes, Place, Vertex Painting, Landscape, Foliage Paint et Geometry Editing.

Les lumières selon leur utilité et leur différences entre statique, stationnaire et dynamique.

Les matériaux via la création de bon nombres d’exemples, comprenant entre autre la Tessellation et le Parallax Occlusion Mapping qui sont deux techniques couramment utilisées dans le jeu vidéo.

Mais aussi les objets 3d pour un usage en temps réel et leur contraintes spécifiques.

Nous aborderons ensuite le blueprint en découvrant les classes, les variables les plus utilisées et par création de plusieurs choses basique comme une lumière, un cycle jour/nuit, un système de sauvegarde très simple nous apprendrons à nous familiarisé avec le langage de programmation “Made In Unreal”. Nous pousserons les choses un peu plus loin avec la création d’une intelligence artificielle que nous programmerons pour qu’elle nous suivre, ou encore qu’elle se rendre à un endroit précis en évitant les différents obstacles.

Nous aborderons les personnages et leurs animations, on créera les différentes mécanique pour faire en sorte d’en faire notre personnage principal.

L’ATH avec deux barres de progression totalement dynamique et deux menus différents. Le menu de démarrage de notre jeu ainsi que le menu pause. Les deux possédant la possibilité de changer la résolution de l’écran ou le niveau des graphismes.

Les véhicules, de la conception 3D à la prise en main.

Les particules en créant de la pluie venant mouiller le sol

le Post Process nous permettant d’obtenir une qualité d’image nettement supérieure grâce à ses différentes options.

Les terrains dans leur intégralité à commencer par l’import en fonction de notre projet, qu’il s’agisse d’un projet basique ou d’un open world, grâce au World Composition.

Mais aussi la conception d’un matériel entièrement automatique qui nous permettra de modeler le terrain en gardant une hiérarchie de texture qui placera l’herbe toujours au dessus, la roche en dessous et la terre entre les deux. Le tout entièrement paramétrable.

Les sons ambiant, la spatialisation ainsi que les bruits de pas à travers la mise en place des types de surfaces et la configuration de nos personnages, qu’il soit en première, jeux de type FPS, ou en troisième personne, GTA entre autre.

La végétation grâce à des modèles créés avec Speedtree et ses effets de vent bien plus poussés que ce qu’Unreal peut nous offrir. Nous créerons un matériel pour notre végétation afin d’en tirer un visuel bien plus réaliste et nous configurerons un tas de paramètres nous permettant notamment de gérer l’interaction avec notre personnage.

Nous terminerons notre cours en apothéose grâce à la conception de deux scène complète, la première, architecturale nous permettra de découvrir quelles sont les options les plus importantes lors de la conception de ce type de scène. Ainsi que le moyen d’obtenir une lumière naturelle avec des ajouts artificiels.

La seconde se voudra plus aérée puisqu’elle sera en extérieure, et comme pour la première, nous aborderons les contraintes de ce genre de scènes afin d’en comprendre la conception.

En toute fin de projet, nous configurerons nos scène pour nous permettre de créer un exécutable pouvant être lancé depuis improviste qu’elle pc doté de Windows 64 bits.

Note importante : Ce cours a été créé en version 4.18.2 et il est préférable d’utiliser LA MEME version ! Si vous choisissez d’utiliser une version plus récente, soyez conscient que vous pouvez rencontrer des erreurs lors de la création ainsi que des options différentes de celles présentées dans le cours.

Who this course is for:

Les utilisateurs débutants souhaitant apprendre l’Unreal Engine
Les utilisateurs intermédiaires souhaitant améliorer leurs compétences
Les utilisateurs avancés souhaitant obtenir des précisions pour fixer leurs acquis.
Basic knowledge
Posséder les connaissances basiques à l’utilisation d’un ordinateur
Winrar ou 7zip (Décompresser les Ressources)
(Facultatif) Un logiciel de modélisation 3d (Blender / 3DS Max / Cinema 4D / Maya…)
(Facultatif) Posséder Open Broadcaster Software (OBS) sur son ordinateur
What will you learn
Prendre en main le logiciel
Créer des matériaux simples et avancés
Programmer des événements et des objets grâce au Blueprint
Importer, configurer et utiliser un personnage
Créer une I.A simple
Créer, configurer et contrôler un véhicule
Importer des terrains propres aux Open World
Connaitre les différents types de lumières et ainsi déterminer facilement lequel est le plus adapté au projet en cours
Créer des scènes architecturales et environnementales
Configurer l’ambiance générale d’un niveau
Créer des menus de démarrages et de pauses
Créer l’executable (.exe) d’un projet
Effectuer des cinématiques simples
Créer une Camera Spectateur avec changement d’option en jeu (Blueprint)

#gamedevelopment #apprendre-lunreal #engine-4

What is GEEK

Buddha Community

Apprendre l'Unreal Engine 4 | Simpliv
Biju Augustian

Biju Augustian

1575978816

Apprendre l'Unreal Engine 4 | Simpliv

Description
Durant ce cours nous aborderont le moteur dans son ensemble. En commençant par le launcher, puis les bases et les principales choses à connaitre comme le déplacement de la caméra, les options les plus courantes. Mais aussi des moyens mémo-technique pour pouvoir très facilement se retrouver dans l’interface de l’Unreal Engine, pas toujours simple quand on débute.

Nous continuerons notre découverte du moteur à travers plusieurs chapitres comprenant les différents modes, Place, Vertex Painting, Landscape, Foliage Paint et Geometry Editing.

Les lumières selon leur utilité et leur différences entre statique, stationnaire et dynamique.

Les matériaux via la création de bon nombres d’exemples, comprenant entre autre la Tessellation et le Parallax Occlusion Mapping qui sont deux techniques couramment utilisées dans le jeu vidéo.

Mais aussi les objets 3d pour un usage en temps réel et leur contraintes spécifiques.

Nous aborderons ensuite le blueprint en découvrant les classes, les variables les plus utilisées et par création de plusieurs choses basique comme une lumière, un cycle jour/nuit, un système de sauvegarde très simple nous apprendrons à nous familiarisé avec le langage de programmation “Made In Unreal”. Nous pousserons les choses un peu plus loin avec la création d’une intelligence artificielle que nous programmerons pour qu’elle nous suivre, ou encore qu’elle se rendre à un endroit précis en évitant les différents obstacles.

Nous aborderons les personnages et leurs animations, on créera les différentes mécanique pour faire en sorte d’en faire notre personnage principal.

L’ATH avec deux barres de progression totalement dynamique et deux menus différents. Le menu de démarrage de notre jeu ainsi que le menu pause. Les deux possédant la possibilité de changer la résolution de l’écran ou le niveau des graphismes.

Les véhicules, de la conception 3D à la prise en main.

Les particules en créant de la pluie venant mouiller le sol

le Post Process nous permettant d’obtenir une qualité d’image nettement supérieure grâce à ses différentes options.

Les terrains dans leur intégralité à commencer par l’import en fonction de notre projet, qu’il s’agisse d’un projet basique ou d’un open world, grâce au World Composition.

Mais aussi la conception d’un matériel entièrement automatique qui nous permettra de modeler le terrain en gardant une hiérarchie de texture qui placera l’herbe toujours au dessus, la roche en dessous et la terre entre les deux. Le tout entièrement paramétrable.

Les sons ambiant, la spatialisation ainsi que les bruits de pas à travers la mise en place des types de surfaces et la configuration de nos personnages, qu’il soit en première, jeux de type FPS, ou en troisième personne, GTA entre autre.

La végétation grâce à des modèles créés avec Speedtree et ses effets de vent bien plus poussés que ce qu’Unreal peut nous offrir. Nous créerons un matériel pour notre végétation afin d’en tirer un visuel bien plus réaliste et nous configurerons un tas de paramètres nous permettant notamment de gérer l’interaction avec notre personnage.

Nous terminerons notre cours en apothéose grâce à la conception de deux scène complète, la première, architecturale nous permettra de découvrir quelles sont les options les plus importantes lors de la conception de ce type de scène. Ainsi que le moyen d’obtenir une lumière naturelle avec des ajouts artificiels.

La seconde se voudra plus aérée puisqu’elle sera en extérieure, et comme pour la première, nous aborderons les contraintes de ce genre de scènes afin d’en comprendre la conception.

En toute fin de projet, nous configurerons nos scène pour nous permettre de créer un exécutable pouvant être lancé depuis improviste qu’elle pc doté de Windows 64 bits.

Note importante : Ce cours a été créé en version 4.18.2 et il est préférable d’utiliser LA MEME version ! Si vous choisissez d’utiliser une version plus récente, soyez conscient que vous pouvez rencontrer des erreurs lors de la création ainsi que des options différentes de celles présentées dans le cours.

Who this course is for:

Les utilisateurs débutants souhaitant apprendre l’Unreal Engine
Les utilisateurs intermédiaires souhaitant améliorer leurs compétences
Les utilisateurs avancés souhaitant obtenir des précisions pour fixer leurs acquis.
Basic knowledge
Posséder les connaissances basiques à l’utilisation d’un ordinateur
Winrar ou 7zip (Décompresser les Ressources)
(Facultatif) Un logiciel de modélisation 3d (Blender / 3DS Max / Cinema 4D / Maya…)
(Facultatif) Posséder Open Broadcaster Software (OBS) sur son ordinateur
What will you learn
Prendre en main le logiciel
Créer des matériaux simples et avancés
Programmer des événements et des objets grâce au Blueprint
Importer, configurer et utiliser un personnage
Créer une I.A simple
Créer, configurer et contrôler un véhicule
Importer des terrains propres aux Open World
Connaitre les différents types de lumières et ainsi déterminer facilement lequel est le plus adapté au projet en cours
Créer des scènes architecturales et environnementales
Configurer l’ambiance générale d’un niveau
Créer des menus de démarrages et de pauses
Créer l’executable (.exe) d’un projet
Effectuer des cinématiques simples
Créer une Camera Spectateur avec changement d’option en jeu (Blueprint)

#gamedevelopment #apprendre-lunreal #engine-4

I am Developer

1611112146

Codeigniter 4 Autocomplete Textbox From Database using Typeahead JS - Tuts Make

Autocomplete textbox search from database in codeigniter 4 using jQuery Typeahead js. In this tutorial, you will learn how to implement an autocomplete search or textbox search with database using jquery typehead js example.

This tutorial will show you step by step how to implement autocomplete search from database in codeigniter 4 app using typeahead js.

Autocomplete Textbox Search using jQuery typeahead Js From Database in Codeigniter

  • Download Codeigniter Latest
  • Basic Configurations
  • Create Table in Database
  • Setup Database Credentials
  • Create Controller
  • Create View
  • Create Route
  • Start Development Server

https://www.tutsmake.com/codeigniter-4-autocomplete-textbox-from-database-using-typeahead-js/

#codeigniter 4 ajax autocomplete search #codeigniter 4 ajax autocomplete search from database #autocomplete textbox in jquery example using database in codeigniter #search data from database in codeigniter 4 using ajax #how to search and display data from database in codeigniter 4 using ajax #autocomplete in codeigniter 4 using typeahead js

Fannie  Zemlak

Fannie Zemlak

1596808440

Cracking The Engineering Management Interview: Part 4

Linkedin, a powerful and effective tool to use during your job hunt process.
Image for post

Photo by Greg Bulla on Unsplash

Introduction

Success has meaning only when we can tie it with a purpose. It’s rewarding to figure out what accomplishments give us a sense of satisfaction — those that deserve us as much as we deserve to work on them. Once we find the problems we are interested in solving, it’s time to put in the work. The importance of tools is paramount in this process. Here I talk about how I used Linkedin as an empowering tool in my job search and interview process.

The more proactive you can be in your job search the better the outcome will be, I speak from personal experience.

I hope you take these ideas, synthesize them into something that applies well to you, make them your own.


Your profile

Be your biggest advocate. Tell the story you want on your profile.

  1. Keep your profile updated. Pick the most significant skills that you think will apply the most in the next job you envision for yourself.
  2. Highlight growth through the list of past experiences. It’s great if you can show that you have been intentional about your career.
  3. Incorporate any talks, papers, blogs that can speak for you. It’s not easy to carve a niche for yourself beyond your role. Thus, it’s really helpful to see how your work connects to that of your community, especially as a leader.
  4. If there are colleagues who can write great things about you, request it via Linkedin. One great one > many good ones(because every accepted Linkedin recommendation is anyways “good”).

Your network

Build your network before you need it. Don’t approach networking with a utilitarian mindset. Go beyond, build a truly rich social circle. Brevity and specificity are your friends here.

  1. Engage with your Linkedin network — congratulate, empathize, communicate personably.
  2. Keep it authentic. There is no reason to fake amicability. Be there when people need you, do what you can. Build your credibility by letting your actions speak for you.
  3. The pedestal of networking is people. Celebrations and professional setbacks — both need people. Having “movers and shakers” in your network speaks about who you are and what kind of people you attract.

Linkedin Jobs

Learn how to navigate and find the jobs relevant to you. Be self-aware to pro-actively seek the right fit. Especially when seeking leadership roles, be mindful of your choices.

  1. Be clear about what you want. Make your job search as efficient as possible by using the right filters. Time is of the essence here.
  2. There comes a certain unique joy in working for a company whose values match yours, I urge you to seek it. Read the company’s core values, see if you think it translates to their products and if they align with you.
  3. Apply to jobs consistently. The dedication helps because there are variables in the equation you might be unaware of and have no control over. Repetition evens out inconsistencies.

Contacting Recruiters

Recruiters are there to help, it’s up to you on how much meaning you can see in these connections. Think longterm.

  1. Connect with the recruiters, be nice to them. They can be your best allies through and through. It’s in your best interest to build the right relationship with them and make them root for you.
  2. I used a template message when I contacted the recruiters and added some personalization touches(name of the recruiter, company) before I sent it out.
  3. I would proactively reach out to two to three recruiters in companies I wished to apply. Sometimes the job lists the recruiter who posted the job — even easier.

Studying The Company and Team

There is no excuse for being company-unaware. Please go through the products, core values, mission of the company before talking to the hiring manager. It just speaks so much about how passionate you are about the role.

  1. Visit their website. Glance through the products, investors, customers, partners, and founders. Check Glassdoor for company reviews.
  2. See if the core values appeal to you, if they indeed translate to their product strategy.
  3. If it’s a startup, visit Crunchbase. See who is funding the company. Try to do some rough math on how financially sound they might be. You will get lots of opportunities to ask good questions throughout your interview. Craft good ones that can teach you more about the future of the company.

Linkedin Premium

Getting Linkedin Premium was one of the best things I gave myself during the job change process. Here are a few reasons why you should consider it.

  1. I was able to send inMail messages to people I was not connected to — key influencers, managers — with messages not restricted by the length of the message.
  2. I used Linkedin Learning which helped me remarkably in honing my skills, broadening my perspectives, polishing my interview delivery styles with the usage of the right words.
  3. Getting access to who visited my profile was helpful sometimes, especially if they worked at a place I admired. It’s a good data point that can go all the way from boosting confidence to making key connections.
  4. Salary insights came handy when negotiating competing offers.

Linkedin Learning

I cannot speak enough about the quality of the material on Linkedin Learning. I have benefited directly from many leadership courses on the Learning platform, especially when I was starting as a manager. Here is how it helped my interviewing process to be precise.

  1. I started using the right words, for example, I used to use “action plan” or “implementation plan”. I started using words like execution, strategy, or tactic, or process. I sounded more professional.
  2. I acquired the subtler skills crucial for a good manager: negotiation skills, managing social capital, persuasion powers, thought leadership. I also expanded my perspective by learning about the mechanics of how to apply them.
  3. It helped me find great books, podcasts from my favorite speakers and coaches. For example, I found Dorie Clark’s courses on Linkedin Learning and connected with her content. That led me to learn more from her work.

#software-engineering #linkedin #linkedin-learning #engineering-leadership #engineering-mangement

Dylan  Iqbal

Dylan Iqbal

1630408920

Big Data Visualization: What, Why, Tips and Tools

Wondering what is big data visualization and how you can apply it for your business? Here's a guide to help you get started.

Because we live in a data-driven society, it’s likely that you’re constantly bombarded with complex sets of data that you need to transmit to your coworkers in an easy-to-grasp way.

The challenge is that almost no one wants to look at large lists of numbers and data, and important information can be easily lost within the midst of chaotic spreadsheets. But there is a solution, and that is big data visualization.

Today, we’ll be covering what big data visualization is and why it’s important, different big data visualization techniques you can use, tips and tricks for creating easily intelligible large data sets and the best big data visualization tools you can use.

By the end of this article, you’ll feel like a real data scientist and be competent in creating pie charts, bar charts, heat maps, histograms, interactive charts and more for big data visualization.

So let’s get into it, shall we?

Table of Contents

What is Big Data Visualization?

Why is Data Visualization Important in Big Data?

What Are the Types of Big Data Visualization?

5 Big Data Visualization Tips for Beginners

4 Tools for Big Data Visualization

---

What is Big Data Visualization?

Big data visualization is the representation of large sets of data through visual aids, whether that be through pie charts, heat maps, bar charts or any other kind of chart types or visual representation.

Analyzing and understanding large data sets and data analytics is no easy task and it can be especially difficult trying to relay that same information to colleagues who are not data-driven or data scientists.

That’s where big data visualization comes in. By transforming your large data sets into visually appealing infographics or interactive charts, you can easily convey your data points to fellow decision-makers.

When your data is plotted out on graphs in a visual way and metrics are made easily readable, no data gets lost in the mix, no matter how large or small, and it makes decision-making for the future a breeze.

Because you can’t make adequate decisions or advance significantly without analyzing your raw data, it’s important that companies use great data visualization methods to keep everyone in the loop.

Let’s take BMW for example.

Image Source

In 2020, BMW was able to track the number of sales for electric cars that they had and then compare it to other car companies’ sales, but not only.

They also were able to track the countries that bought the highest amount of their electric cars.

Image Source

This is a prime example of big data visualization in action. When you track your analytics and data, you can see where your wins are and when to celebrate or where your losses are and how you can make adjustments for the future.

Now, imagine for a moment that all this information was just written out plainly on a spreadsheet and had unstructured data all over it.

It would be hard to understand and assess how the company is doing and would take a long time to communicate to employees how their work has affected the sales of the cars.

This is why visualizing big data is so important. With just a glance and within seconds, you can easily see what cars are selling best and in what countries.

No time is wasted going through spreadsheets and trying to make sense of unstructured data — just visual analytics laid out for all to see and understand.

 

Why is Data Visualization Important in Big Data?

We live in a time where the internet and social media have exploded at an extraordinary rate, and information can be gathered within seconds and at the tips of anyone’s fingers.

With the rise of this technological era, it’s important that data can be visualized and consumed quickly and efficiently — especially since the human brain now has an attention span of about 8 seconds, according to this study by the Technical University of Denmark.

Because companies, businesses and organizations can gather data more quickly than ever, this means that they need to be able to visualize that data in an equally quick and easily consumable way.

The best way to efficiently communicate your ever-coming, new data is through visualizing big data. This will bring your complex data to life and anyone who looks at it will be able to understand and grasp it with just a glance.

Customize this template and make it your own!

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Take the image above as an example. With just a quick look at the statistics that are clearly visualized, you can make a data-based assumption.

Now, imagine if this data was just written out plainly on a spreadsheet. It would take much longer to understand and make an assumption based on the numbers.

By using big data visualization techniques, you’ll be able to get the most value from your data and analytics and make sure that everyone who says your data analysis will be able to interpret, understand and use your data. This, in turn, will help your company excel.

When you use data visualization techniques, it will optimize your use of data, help decision making and planning go smoothly, you’ll be able to identify and mitigate risk, extract loads of useful data and insights and improve your overall strategy and direction of your company.

There are no losses to using a visual representation of data, only wins. But there are lots of different types of data visualization that you can use.

Let’s discuss the different types of big data visualization and assess which one will work best for you.

 

What Are the Types of Big Data Visualization?

There are lots of different types of data visualization that data analysts like to use and depending on the amount of data. A data analyst may choose to use a pie chart to express their numerical data or a bar chart.

When looking at big data analytics regarding locations, one might choose to use an interactive heat map or maybe a pivot table.

We’re going to look at 8 common types of big data visualization and some data visualization examples for each to help you decipher which one will work best for you.

 

Type #1: Line Charts

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A line chart, also known as a line graph, is a graphic representation of data that plots a fixed value on one side and a variable on the other.

A line chart is a fantastic way to represent the relationship of data. You can use a line chart to represent changes and fluctuations of things within a certain period of time.

 

Type #2: Bar Charts

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A bar chart, also known as a bar graph, uses bars to compare different data points or data sets.

Many data scientists will use bar charts to visually represent their data analysis. You can use a bar chart to compare large amounts of data, fluctuations of quantities or different categories.

The taller the bar, the larger the numerical value and vice versa.

 

Type #3: Pie Charts

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Pie charts, donut charts, circle graphs or whatever you choose to call them, are representations of data that are split into smaller segments and sizes to represent their numerical value.

When you use a pie chart, it becomes easy to see and compare how the different segments relate and differ from each other.

When using a pie chart, try not to overload it with too many different values. When you split the pie chart into more than 7 segments, it can become difficult to understand the data.

 

Type #4: Heat Maps

Image Source

A heat map is a visual representation of data that is laid out on a map or table and uses different nuances and intensities of colors to represent its data.

Using a heat map can be especially helpful when you need to analyze data that seems to be never-ending. When you have an extremely wide value range, using a heat map makes it much more simple to quickly visualize and analyze large amounts of complex data at a glance.

 

Type #5: Histograms

histogram - weights of newborns

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A histogram is a graphical and visual representation of complex data sets and the frequency of said numerical data displayed through bars.

Histograms are very similar to bar graphs but vary in the fact that they mostly focus on the repeated frequency of numerical data.

Type #6: Scatter Plots

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A scatter plot, scatter chart or scatter graph, is a diagram that uses dots to represent and emphasize the different values of two or more numeric variables on an X and Y-axis.

Scatter plots are extremely useful to use when you have multiple large data sets and you want to know how they relate to each other and compare the importance of each value.

 

Type #7: Treemaps

Create your own charts and graphs!

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Treemaps are the visual representation of hierarchical data by using color-coded rectangles.

Users can use treemaps as a method to compare multiple sets of data and reflect the weight of each value in a project.

 

Type #8: Funnel Charts

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Funnel charts are typically used in sales and represent the different stages that your users or customers go through during the sales process and demonstrate decreasing values as they move through your funnel.

By using a funnel chart, you can accurately see where you are losing or gaining your customers during the sales process.

 

5 Big Data Visualization Tips for Beginners

Now that we’ve covered what big data visualization is, its importance and 9 different types of data visualization, you may feel like you’re a professional in data science.

Now that you’re familiar with the basics of data visualization, it’s time that we equip you with some of our best data visualization techniques.

Here are our top 5 best data visualization techniques for you to use when creating a visual representation of your data.

 

Tip #1: Use a Powerful Data Visualization Tool

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You can’t create powerful graphs without a powerful data visualization tool.

Sure, you could use something like Google charts, but to create unique, engaging charts, you’ll want to use a data visualization tool like Visme that's packed with amazing functionality.

Visme is a powerful data visualization tool with many integration functionalities. As you can see in the image above, you can create everything from funnel charts and tables to interactive data maps and graphs in this editor.

When you need to visualize big data, Visme is the way to go. When you create a graph in our big data visualization tool, your data can be updated in real-time with our integration tools.

You can import all your data from Google Sheets, Microsoft Excel, Google Analytics and other data sources, then see it come to life automatically on your project while you sit back and relax.

Visme also has many open-source elements and graphics for you to use to keep your infographic intriguing. To have the perfect interactive data visualization, you can use word clouds, tables, treemaps, animated characters and graphic design elements and more to implement into your design.

They’re also a powerhouse filled with lots of useful and educational tutorials on how to create the perfect chart for your raw data. Visme also has lots of tutorials for all things graphic design.

So why not use a tool that has everything you need for creating visuals for your data analysis and tons of tutorials to go with it? You can start your free account with Visme today and start living out your data analyst dreams.

It’s important to use a strong data visualization software for your data analysis and presentations. Stick around and soon we’ll get into our list of best tools for big data visualization.

 

Tip #2: Pick the Correct Form of Big Data Visualization

Customize this template and make it your own!

Edit and Download

When it comes to visualizing your data, you need to make sure that you choose the correct chart type.

Because there are so many different ways to display your data, you need to weigh out the cons and pros of each and find out which one will work best for your infographic or presentation.

Take for example pie charts and bar graphs.

When you analyze data that is very different, you might want to use a pie chart. But if you want to represent data entries that are close together, you could use a bar chart for that.

If you’re trying to create data visualization for sales, you could use a funnel chart, pyramid chart or cone chart for that.

Each different visualization method has its time and place, and you need to analyze your data and think about what method will work best for your respective data.

Refer above to the “Big Data Visualization Types” section above to see which one will suit you best.

 

Tip #3: Make Sure Your Data is Easily Comprehensible

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The whole point of big data visualization is to make it easy to understand at a glance.

It won’t be easily intelligible if you just start piling in large amounts of unstructured data and simply hope for the best. Or imagine you have tens of tiny little numbers on a bar graph that no one can see or read.

You need to make sure that anyone on your team, whether a data scientist or not, can understand what you’re trying to convey at a glance.

You can do this by using clear and bold text, contrasting font colors and background colors, not adding too many values to one chart and using compelling images to highlight your point, just like in the example above.

By adding too much text or too many values to a single graph, you risk confusing your audience even more. So keep it as simple and concise as possible.

 

Tip #4: Always Use Legends to Further Explain Your Data

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Using legends is absolutely vital for making your data easy to understand, so whether you’re creating a pie chart or bar graph, make sure you’re using a legend.

A legend is an area of your design that further explains each segment of your chart.

Many times people will assign a color to a segment in their chart, just like in the example above, and on the side add a little graphic element that explains what each color represents.

The legend is responsible for keeping the audience engaged and understanding everything you’re trying to convey.

 

Tip #5: Use Multiple Charts for Big Data

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If you have a large amount of data that needs to be conveyed to your team, try using multiple graphs to do so.

Incorporating tons of data into a single chart will only make it hard for the human brain to stay on track and focus to try and understand what you want to share.

The best rule of thumb to follow here is KISS — keep it simple, stupid.

So instead of simply adding all your data to one pie chart and making it have 30 pie slices, why not create multiple graphs and break it down into bite-sized pieces? Pun intended.

By creating multiple matching charts, you can keep your data easily intelligible, cohesive and right on brand.

Just like in the example above, you can clearly understand all the data that’s being displayed because it is written out on two different donut charts.

You want to make sure your information is understandable by anyone at a glance, and you can do so by breaking down your data.

 

4 Tools for Big Data Visualization

Now that you know essentially all there is to know about big data visualization, it’s time you choose a tool that will help you create those visuals.

We’ll be covering 4 data visualization software you can use to get the job done.

Let’s jump right into it.

 

Tool #1: Visme

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If you want to create compelling and professional data visualization, then you need a tool like Visme.

Visme makes it easy for both designers and non-designers alike to visualize their data in interactive and engaging ways.

For example, you can create incredible animated charts, add your own audio files to them that you can record right within the editor, add tons of professionally design data widgets and import all your data from third-party websites such as Microsoft Excel, Google sheets etc.

The best part? You can save endless amounts of time and effort by using one of our hundreds of customizable templates for displaying your data.

Simply scroll through tons of professionally design templates for charts and data choose one that suits your style.

Everything can be customized on each and every template and you can even add your own brand colors, logo and font to keep everything right on-brand with your other designs.

Not only can you create loads of beautiful charts, graphs and infographics with Visme, but you can also create anything else design-related. You can create presentations, infographics, multi-page reports and proposals, branded social graphics and more.

If you’re looking for a powerful data visualization tool with high functionality for many other types of designs, Visme is the one for you. Plus, you can create a free account and use for as long as you like — no trial period or hidden costs!

 

Tip #2: Tableau

Tableau is an interactive data visualization software with a focus on business intelligence. Their goal is to help people make data that can be easily understood by anyone.

Tableau is a tool that is used in the business intelligence industry and it can help you simplify raw data into a simple format. With drag and drop functionalities, you can create data visualization fairly quickly and then share it with others.

In Tableau you can create lots of different data visualizations, from a correlation matrix to a simple bar graph.

Another plus for the software is that you can infuse the Tableau dashboard with artificial intelligence and machine learning from Aible.

You can start a free trial with Tableau, but it is a bit pricey after your trial is up. At $70/month billed annually, you’ll have to make sure you absolutely love the product before buying it.

 

Tool #3: Microsoft’s Power BI

Power BI by Microsoft is a business analytics service that helps you create interactive data visualizations.

Whether your data is on an Excel spreadsheet an on-premises hybrid data warehouses, Power BI will help you bring that data together to create reports and graphs to share with your team.

There are three versions of Power BI that you can use: the desktop app, the mobile app or their website.

You can use Power BI to help you visualize big data with your team by using some of their other popular apps like Microsoft Excel and work together in real-time to create compelling data.

Power BI has some basic templates that you can use to get a jump start on creating your data.

Power BI is quite affordable, coming in at $9.99/month.

If you’re not completely sold on using Power BI, let’s move on to our next tool.

 

Tool #4: Datawrapper

Datawrapper is an online tool that you can use to create data visualizations that are interactive and responsive, with no code or programming languages like python or javascript required.

With big users like the New York Times and the UN, they do have quite a few things to boast about.

Data wrapper is an open-source and easy-to-use data visualization software where you can create basic charts and graphs, maps and line charts that can be embedded into your website.

As for the price, you can use their free plan and create lots of charts, maps and tables, but they will be watermarked and there are a few other inconveniences that come with the free plan.

The next plan comes in at $599/month, which is definitely on the pricey side.

And that concludes our list of 4 tools for data visualization.

 

Now Over to You

If you want a data visualization software that will help you convey your data in a fun and engaging way, then you most likely will love using Visme.

Not only is Visme a powerful data visualization tool, but it’s so much more. You can use Visme to create all of your graphic design needs, from sales presentations to pitch decks, social media posts, infographics, videos, eBooks and more.

What are you waiting for? Create your free account today and free your inner data scientist.

Originally published at https://visme.co

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Siphiwe  Nair

Siphiwe Nair

1624072920

10 Must-have Skills for Data Engineering Jobs

Big data skills are crucial to land up data engineering job roles. From designing, creating, building, and maintaining data pipelines to collating raw data from various sources and ensuring performance optimization, data engineering professionals carry a plethora of tasks. They are expected to know about big data frameworks, databases, building data infrastructure, containers, and more. It is also important that they have hands-on exposure to tools such as Scala, Hadoop, HPCC, Storm, Cloudera, Rapidminer, SPSS, SAS, Excel, R, Python, Docker, Kubernetes, MapReduce, Pig, and to name a few.

Here, we list some of the important skills that one should possess to build a successful career in big data.

1. Database Tools
2. Data Transformation Tools
3. Data Ingestion Tools
4. Data Mining Tools

#big data #latest news #data engineering jobs #skills for data engineering jobs #10 must-have skills for data engineering jobs #data engineering