#data analytics visualization

[analyticsliv]

GA4 is a powerful tool but only if you know how to use it. Investing in Google Analytics 4 consulting services is more than a technical decision; it's a strategic move toward sustainable growth. From setting up accurate tracking and visualizing performance to navigating privacy regulations and optimizing marketing, GA4 consultants provide critical support at every step.

[softwaredevelopment23]

D3 Is Taking Over & Here’s What Your Data Analytics And Visualization Is Missing

D3.js, short for Data-Driven Documents, is a sophisticated JavaScript library that empowers developers to animate data with life through HTML, SVG, and CSS. D3 enables the creation of stunning visuals from basic bar graphs to intricate interactive maps, transforming raw data into visual narratives.

[saraharveypatrick]

Ninja, robots, pirates, magic

I made an interactive visualization on the 100 most popular comics at the Brooklyn Public Library for January 2025. The full 100 is also here on Medium. Top manga 1. Demon slayer = Kimetsu no yaiba Volume 1 by Koyoharu Gotoge, 2019 2. One piece by Eiichirō Oda, 2023 3. Spy x family. 1, Mission 1 by Tatsuya Endo, 2020 4. My hero academia. Vol. 1, Izuku Midoriya: Origin by Kōhei Horikoshi, 2015 5. Spy x family. Vol. 12 by Tatsuya Endō, 2024 6. Demon slayer. 23, Life shining across the years by Koyoharu Gotoge, 2021 7. Naruto. Vol. 1, The tests of the ninja by Masashi Kishimoto, 2023 8. Jujutsu kaisen. Volume 1, Ryomen Sukuna by Gege Akutami, 2019 9. Spy x family. Volume 11 by Tatsuya Endō, 2024 10. Dragon ball super. 1, Warriors from Universe 6! by Akira Toriyama, 2017

Top Marvel checkouts

Guardians of the Galaxy Volume 3, DVD, 2023

Ant-Man and the Wasp: Quantumania, DVD, 2023

Miles Morales, Straight out of Brooklyn by Saladin Ahmed, 2019

Black Panther: Wakanda Forever, DVD, 2021

Spider-Man: No Way Home, DVD, 2022

Doctor Strange in the Multiverse of Madness, DVD, 2022

Ms. Marvel. 1, No normal by G Willow Wilson, 2014

Spider-Man. Vol. 1, Miles Morales by Brian Michael Bendis, 2016

Thor: Love and Thunder, DVD, 2022

Other graphic novels

Heartstopper Volume 5 by Alice Oseman, 2023

Heartstopper Volume 2 by Alice Oseman, 2020

Heartstopper Volume 3 by Alice Oseman, 2021

Heartstopper Volume 4 by Alice Oseman, 2021

The Girl From the Sea by Molly Knox Ostertag, 2021

The Twisted Ones by Scott Cawthon, 2021

Five Nights at Freddy’s, Fazbear Frights, The Fourth Closet by Chris Hastings, 2022

Heartstopper Volume 1 by Alice Oseman, 2020

Five Nights at Freddy’s, Fazbear Frights, Graphic Novel Collection Vol. 1 by Scott Cawthon, 2022

The Princess and the Grilled Cheese Sandwich by Deya Muniz, 2023

[scipunk]

Alien: Covenant (2017) - UIs

[capitalism-and-analytics]

For anyone currently in school or recently in school

I am doing a few guest lectures at some of the universities in my state and working on my presentation. Curious if anyone has any recommendations of topics they really enjoyed from a past guest speaker that isn't major/field-specific?

[samvavlabs]

Data Analyst Roadmap for 2024!

Cracking the Data Analyst Roadmap for 2024! Kick off your journey by mastering and delving into Python for data manipulation magic, and dazzle stakeholders with insights using PowerBi or Tableau. Don't forget, that SQL proficiency and hands-on projects refine your skillset, but never overlook the importance of effective communication and problem-solving. Are you checking off these milestones on your path to success? 📌 For more details, visit our website: https://www.samvavlabs.com  . . . #DataAnalyst2024 #CareerGrowth #roadmap #DataAnalyst #samvavlabs #roadmap2024 #dataanalystroadmap #datavisualization

[uthra-krish]

The Skills I Acquired on My Path to Becoming a Data Scientist

Data science has emerged as one of the most sought-after fields in recent years, and my journey into this exciting discipline has been nothing short of transformative. As someone with a deep curiosity for extracting insights from data, I was naturally drawn to the world of data science. In this blog post, I will share the skills I acquired on my path to becoming a data scientist, highlighting the importance of a diverse skill set in this field.

The Foundation — Mathematics and Statistics

At the core of data science lies a strong foundation in mathematics and statistics. Concepts such as probability, linear algebra, and statistical inference form the building blocks of data analysis and modeling. Understanding these principles is crucial for making informed decisions and drawing meaningful conclusions from data. Throughout my learning journey, I immersed myself in these mathematical concepts, applying them to real-world problems and honing my analytical skills.

Programming Proficiency

Proficiency in programming languages like Python or R is indispensable for a data scientist. These languages provide the tools and frameworks necessary for data manipulation, analysis, and modeling. I embarked on a journey to learn these languages, starting with the basics and gradually advancing to more complex concepts. Writing efficient and elegant code became second nature to me, enabling me to tackle large datasets and build sophisticated models.

Data Handling and Preprocessing

Working with real-world data is often messy and requires careful handling and preprocessing. This involves techniques such as data cleaning, transformation, and feature engineering. I gained valuable experience in navigating the intricacies of data preprocessing, learning how to deal with missing values, outliers, and inconsistent data formats. These skills allowed me to extract valuable insights from raw data and lay the groundwork for subsequent analysis.

Data Visualization and Communication

Data visualization plays a pivotal role in conveying insights to stakeholders and decision-makers. I realized the power of effective visualizations in telling compelling stories and making complex information accessible. I explored various tools and libraries, such as Matplotlib and Tableau, to create visually appealing and informative visualizations. Sharing these visualizations with others enhanced my ability to communicate data-driven insights effectively.

Machine Learning and Predictive Modeling

Machine learning is a cornerstone of data science, enabling us to build predictive models and make data-driven predictions. I delved into the realm of supervised and unsupervised learning, exploring algorithms such as linear regression, decision trees, and clustering techniques. Through hands-on projects, I gained practical experience in building models, fine-tuning their parameters, and evaluating their performance.

Database Management and SQL

Data science often involves working with large datasets stored in databases. Understanding database management and SQL (Structured Query Language) is essential for extracting valuable information from these repositories. I embarked on a journey to learn SQL, mastering the art of querying databases, joining tables, and aggregating data. These skills allowed me to harness the power of databases and efficiently retrieve the data required for analysis.

Domain Knowledge and Specialization

While technical skills are crucial, domain knowledge adds a unique dimension to data science projects. By specializing in specific industries or domains, data scientists can better understand the context and nuances of the problems they are solving. I explored various domains and acquired specialized knowledge, whether it be healthcare, finance, or marketing. This expertise complemented my technical skills, enabling me to provide insights that were not only data-driven but also tailored to the specific industry.

Soft Skills — Communication and Problem-Solving

In addition to technical skills, soft skills play a vital role in the success of a data scientist. Effective communication allows us to articulate complex ideas and findings to non-technical stakeholders, bridging the gap between data science and business. Problem-solving skills help us navigate challenges and find innovative solutions in a rapidly evolving field. Throughout my journey, I honed these skills, collaborating with teams, presenting findings, and adapting my approach to different audiences.

Continuous Learning and Adaptation

Data science is a field that is constantly evolving, with new tools, technologies, and trends emerging regularly. To stay at the forefront of this ever-changing landscape, continuous learning is essential. I dedicated myself to staying updated by following industry blogs, attending conferences, and participating in courses. This commitment to lifelong learning allowed me to adapt to new challenges, acquire new skills, and remain competitive in the field.

In conclusion, the journey to becoming a data scientist is an exciting and dynamic one, requiring a diverse set of skills. From mathematics and programming to data handling and communication, each skill plays a crucial role in unlocking the potential of data. Aspiring data scientists should embrace this multidimensional nature of the field and embark on their own learning journey. If you want to learn more about Data science, I highly recommend that you contact ACTE Technologies because they offer Data Science courses and job placement opportunities. Experienced teachers can help you learn better. You can find these services both online and offline. Take things step by step and consider enrolling in a course if you’re interested. By acquiring these skills and continuously adapting to new developments, they can make a meaningful impact in the world of data science.

[khushidubeyblog]

[mokkup-ai]

You still been using outdated design tools to create dashboard mockups? 🥴 OOF. Issokay We've all been there.

Now create hi-fi dashboard wireframes with Mokkup.ai in under 30 mins. Share, comment, export and present your designs to the world! 🌎

[anishmary]

From Zero to Hero: Mastering Data Analytics for Transformation

The concept of "data" has enormous significance in the modern digital world. The enormous amount of information produced every day has revolutionized the way we view the world and move through it. The data analytics industry is one of the major players in this revolution. Let's set out on an adventure to discover the fundamentals of data analytics, consider their importance, and understand how they affect different facets of our lives.

Understanding Data Analytics Analyzing massive data sets to find hidden patterns, correlations, trends, and insights is at the heart of data analytics. It's like sorting through a gold mine of knowledge to find the gold nuggets that will help you make decisions and solve problems. Data analytics isn't just about statistics and figures; it's about turning raw data into compelling narratives that encourage informed decisions.

Why Data Analysis Is Important

The capacity to make sense of all the data in the globe has changed the game. Data analytics enables companies, groups, and people to comprehend their operations, clients, and environments more thoroughly. Here are a few main arguments in favor of data analytics:

Making Informed Decisions: Data-driven insights allow for more precise and knowledgeable decision-making. Companies might modify their tactics in light of current developments and customer preferences.

Enhanced Efficiency: Data analytics uncovers bottlenecks and inefficiencies in processes and operations, allowing for focused changes.

Predictive Skills: By analyzing past data, predictive models can predict future patterns and aid organizations in becoming ready for the future.

Customer insights: Data analytics reveals the preferences and habits of customers, enabling more individualized interactions and higher levels of customer satisfaction.

Risk Management: Identifying potential risks and fraud patterns is made easier with data analytics, reducing vulnerabilities and losses.

Scientific Discoveries: In fields like healthcare and research, data analytics aids in uncovering groundbreaking insights and advancements.

The Data Analytics Process

Data analytics involves a systematic approach that follows several key steps:

Defining Objectives: Clearly state the objectives and issues you hope to resolve through data analysis.

Data Collection: Collect pertinent data from a variety of sources, making sure it is reliable and representative. Data Cleaning: Involves altering it to ensure accurate analysis.

Exploratory Analysis: Investigate the data in depth to find patterns, trends, and early insights.

Modeling: Building statistical models or algorithms to forecast outcomes or comprehend correlations in the data is known as modeling.

Interpretation: Draw conclusions from your analysis's findings and connect them to your original goals.

Visualization: To make your findings easier to understand, present them using visual tools like charts, graphs, and dashboards.

Action: Implement the learnings from data analysis to inspire positive changes and actions.

Data analytics has become an effective means for turning data into useful insights. By bridging the gap between information overload and useful knowledge, it facilitates decision-making, ignites innovation, and opens doors. A fascinating and fruitful trip may be had by anyone interested in learning more about data analytics, whether they are a business owner, researcher, or just curious. So, take part in uncovering the secrets of the data and grasp the power of data analytics to transform. If you need help implementing data analytics in your organization or if you want to learn more, you should consult professionals or sign up for specialized courses. For instance, the ACTE Institute offers comprehensive data analytics training courses that can provide you the knowledge and skills you need.

[analyticsliv]

Data driven attribution employs real-time data and machine learning to assign value to each touchpoint in the customer journey. This, in turn, helps brands make intelligent marketing decisions, reduce wasteful ad spends, and enhance their Conversion Rate Optimization Services.

[corpusdigitalhub]

Mastering Data Analytics: Your Path to Success Starts at Corpus Digital Hub

Corpus Digital Hub is more than just a training institute—it's a hub of knowledge, innovation, and opportunity. Our mission is simple: to empower individuals with the skills and expertise needed to thrive in the fast-paced world of data analytics. Located in the vibrant city of Calicut, our institute serves as a gateway to endless possibilities and exciting career opportunities.

A Comprehensive Approach to Learning

At Corpus Digital Hub, we believe that education is the key to unlocking human potential. That's why we offer a comprehensive curriculum that covers a wide range of topics, from basic data analysis techniques to advanced machine learning algorithms. Our goal is to provide students with the tools and knowledge they need to succeed in today's competitive job market.

Building Strong Foundations

Success in data analytics begins with a strong foundation. That's why our courses are designed to provide students with a solid understanding of core concepts and principles. Whether you're new to the field or a seasoned professional, our curriculum is tailored to meet your unique needs and aspirations.

Hands-On Experience

Theory is important, but nothing beats hands-on experience. That's why we place a strong emphasis on practical learning at Corpus Digital Hub. From day one, students have the opportunity to work on real-world projects and gain valuable experience that will set them apart in the job market.

A Supportive Learning Environment

At Corpus Digital Hub, we believe that learning is a collaborative effort. That's why we foster a supportive and inclusive learning environment where students feel empowered to ask questions, share ideas, and explore new concepts. Our experienced faculty members are dedicated to helping students succeed and are always available to provide guidance and support.

Cultivating Future Leaders

Our ultimate goal at Corpus Digital Hub is to cultivate the next generation of leaders in data analytics. Through our rigorous curriculum, hands-on approach, and supportive learning environment, we provide students with the tools and confidence they need to excel in their careers and make a positive impact on the world.

Join Us on the Journey

Are you ready to take the next step towards a brighter future? Whether you're a recent graduate, a mid-career professional, or someone looking to make a career change, Corpus Digital Hub welcomes you with open arms. Join us on the journey to mastery in data analytics and unlock your full potential.

Contact Us Today

Ready to get started? Contact Corpus Digital Hub to learn more about our programs, admissions process, and scholarship opportunities. Your journey towards success starts here!

Stay connected with Corpus Digital Hub for the latest news, updates, and success stories from our vibrant community of learners and educators. Together, we'll shape the future of data analytics and make a difference in the world!

[newfangled-vady]

Top 5 Benefits of Low-Code/No-Code BI Solutions

Low-code/no-code Business Intelligence (BI) solutions offer a paradigm shift in analytics, providing organizations with five key benefits. Firstly, rapid development and deployment empower businesses to swiftly adapt to changing needs. Secondly, these solutions enhance collaboration by enabling non-technical users to contribute to BI processes. Thirdly, cost-effectiveness arises from reduced reliance on IT resources and streamlined development cycles. Fourthly, accessibility improves as these platforms democratize data insights, making BI available to a broader audience. Lastly, agility is heightened, allowing organizations to respond promptly to market dynamics. Low-code/no-code BI solutions thus deliver efficiency, collaboration, cost savings, accessibility, and agility in the analytics landscape.

[mobio-solutions]

🚀 Dive into the Future of Supply Chain & Logistics! Discover how advanced supply chain analytics is reshaping the way we manage logistics and supply chains. From predicting trends to optimizing routes, these smart tools are not just about crunching numbers – they're reshaping how we think about and manage the flow of goods. 📦

[capitalism-and-analytics]

[digital-marketing-insight]

Navigating Real-Time Operations: The Power of Operational Dashboards

Operational dashboards are dynamic visual interfaces that provide real-time insights into an organization's day-to-day activities and performance. These dashboards are particularly valuable for monitoring short-term operations at lower managerial levels, and they find application across various departments. They stand as the most prevalent tools in the realm of business intelligence.

Typically, operational dashboards are characterized by their comprehensive nature, offering junior managers detailed information necessary to respond to market dynamics promptly. They also serve to alert upper management about emerging trends or issues before they escalate. These dashboards primarily cater to the needs of managers and supervisors, enabling them to oversee ongoing activities and make rapid decisions based on the presented information. Operational dashboards often employ graphical representations like graphs, charts, and tables and can be customized to display information pertinent to the specific user.

Examples of data typically showcased on an operational dashboard include:

Sales figures

Production metrics

Inventory levels

Service levels

Employee performance metrics

Machine or equipment performance data

Customer service metrics

Website or social media analytics

It is crucial to emphasize that operational dashboards are distinct from other dashboard types, such as strategic and analytical dashboards. These different dashboards serve varied purposes and audiences and contain dissimilar datasets and metrics. Here are a couple of examples. 

Below, you can see a Revenue overview dashboard for QuickBooks. It provides month-by-month overviews of invoices, products, customers, profit and loss. Such a dashboard can be used on a daily basis and help monitor and manage operating activities. 

This data visualization is connected to a data automation solution, Coupler.io. It automatically transfers fresh data from QuickBooks to the dashboard, making it auto-updating. Such a live dashboard can be an important instrument for enabling informed decision-making.

This Revenue overview dashboard is available as a free template. Open it and check the Readme tab to see how to use it.

Here’s another example of an operational dashboard, the Facebook Ads dashboard. It allows ad managers to closely track their ad performance. This dashboard is also powered by Coupler.io, so it depicts ad data in near real-time. This allows marketers to quickly define what works and what doesn’t and make adjustments on the go.

Facebook Ads dashboard is available as a free template. You can grab it and quickly get a copy of this dashboard with your data. In conclusion, operational dashboards are indispensable tools for organizations seeking to thrive in a dynamic business landscape. These real-time visual displays offer invaluable insights into day-to-day operations, equipping managers and supervisors with the information to make swift, informed decisions. As the most widely used business intelligence instruments, operational dashboards empower businesses to adapt to market changes, identify emerging trends, and maintain a competitive edge. Their versatility and capacity to monitor a wide range of metrics make them an essential asset for managing the intricacies of modern operations.