Data has become an organization's valuable asset as it helps businesses draw data-driven insights and observe trends to optimize workflow. However, with an unprecedented amount of data, it is essential to visualize data clearly and concisely. This is where the role of big data visualization tools comes into the picture. It equips your organization with transformative tools to visualize complex data effortlessly.
This article will delve deeper into different big data analytics visualization tools you can employ for day-to-day business activities. These tools come with various features to cater to your specific business requirements. So, without further delay, let’s get started.
Overview of Data Visualization
Data visualization represents data and information in a graphical format, such as graphs, charts, dashboards, and other visual formats. It facilitates the effortless transformation of complex data into easily understandable visuals. You can use these visualizations to discover patterns, identify trends, and derive actionable insights from a dataset. In other words, it adds depth to your decision-making process by presenting data in a structured and visually appealing manner.
Top 6 Tools for Big Data Visualization
Now that you have understood the importance of data visualization, you should familiarize yourself with the big data tools to unlock the power of your dataset.
Power BI
Developed by Microsoft, Power BI is a software application that enables you to transform disparate data sources into cohesive, interactive, and captivating insights. It has data modeling skills and visualization avenues, ranging from simple charts to complex illustrations. For instance, you can gain a comprehensive knowledge of significant KPIs and indicators to understand the company’s success and assist management in making decisions and developing long-term plans.
Key Features:
- Data Connectivity: It provides various options for connecting to different data sources, including Excel spreadsheets, cloud-based databases, and on-premises data.
- User Friendly: With a wide range of functions from simple data modeling to complex analytics, the Power BI tool is tailored to benefit experienced and novice users.
- Data Transformation with Power Query: Power Query is a powerful tool for performing ETL data processing. It has a power query editor interface to import data from multiple sources to perform transformations such as filtering rows and columns. You can also perform advanced transformations like pivoting, grouping, and text manipulation.
- Updates Data Automatically: You may eliminate time-consuming manual report updates using Power BI’s scheduled refresh feature. It helps to automate your data pipelines by defining the frequency and time slots to refresh the data. Although the aim is to refresh your data within 15 minutes of the scheduled time, in rare cases, you can expect a delay of up to one hour.
Tableau
Tableau is an incredible business intelligence and data visualization application for reporting and assessing large volumes of data. It helps you to create charts, graphs, maps, and dashboards to display and analyze data effectively.
Key Features:
- Dynamic Dashboards: Tableau allows you to construct visuals that include drill-down capabilities, visual isolation of specific data subsets, data order modification, and many other features.
- Enhanced Data Reliability: Tableau Catalog automatically catalogs all your data sources and assets for quick discovery. It also offers metadata within Tableau to help you understand and trust the data you consume.
- Data Exploration: Defining relationships in your data can be tedious, but the Explain Data feature simplifies this process. You can swiftly delve deeper into the datasets to discover essential data points.
Qlik Sense
Qlik Sense is a popular analytics platform because of its in-memory data processing, which makes data manipulation and analysis faster. The application allows data visualization from several sources and encourages in-depth analysis, making creating solid and intuitive data visualizations easier. With a user-friendly interface, Qlik Sense promotes self-service data recovery by empowering you to design your dashboards and reports for analysis.
Key Features:
- Augmented Data Analysis: Qlik Sense has a wide range of capabilities for augmented data analytics. This feature lets you combine human and artificial intelligence to make simple and visual interactions with data. You can ask queries regarding data, and it will automatically generate insights by analyzing the data.
- Alerting and Automation: Qlik has an alerting feature that helps you monitor your datasets. You can instantly respond to the changes made in your data and keep track of them. Moreover, you can also automate your routine tasks and synchronize your key tools to work with analytics.
- Customized Applications and Add-ons: Qlik Sense includes various add-ons like Qlik.dev, which integrates Qlik with custom business applications, API references, and developer documentation. Additionally, you can incorporate plug-ins like Visual Basic and employ server-side, write-back, and visualization extensions for analysis within the Qlik Sense application.
Sisense
Sisense is a highly intuitive and adaptable data visualization tool that facilitates seamless data consolidation, analysis, and visualization. It helps you turn complicated data into significant insights you can share or embed anywhere. Sisense aims to assist you in making well-informed decisions by offering a straightforward interface for reporting and data research.
Key Features:
- High Scalability: Sisense is easily scalable to meet your expanding needs and data quantities. Whether your company is a small corporation or a large enterprise, it is built to reshape according to requirements.
- AI and Machine Learning Capabilities: Sisense facilitates data forecasting and predictive analytics to help you anticipate future market trends and make farsighted decisions using the potential of AI and machine learning tools.
- Enhanced Data Security: Sisense has many data security and governance features to ensure your data is protected and consistent with relevant regulations. It uses various encryption technologies like SHA-256 and TripleDES to secure account credentials and authorization.
Zoho Analytics
Zoho Analytics is a data reporting and visualization application that makes it simple to create engaging dashboards. You can track essential performance indicators, spot anomalies, anticipate the future, and identify undiscovered insights using the analytics system.
Key Features:
- Unified Business Insights: By combining data from several teams, like sales, marketing, finance, and support, Zoho Analytics enables you to unify your business data. It also provides easy connectivity, pre-built analytics, and smart data integration capabilities for a smooth study of the unified data with distinctive end-to-end insights.
- Data Security: Zoho Analytics offers security practices, which include continuous support for regular data backups, data confidentiality, design privacy, and a clear separation of roles in the workspace.
- Easy Deployment: It provides alternatives for deployment on public clouds such as Azure, AWS, and Google, in addition to its cloud-based analytics software subscriptions.
Looker
Provided by Google, Looker is an integrated self-service analytics platform that lets you build reports from several data sources and optimize workflows. It is a multi-cloud unified platform offering data visualization for on-premise databases like MariaDB and PostgreSQL and cloud-based platforms like Azure.
Key Features:
- Intuitive User Interface: It is very convenient to set up and use Looker as it allows you to build custom data models and draft reports. It offers dashboards with customized charts, graphs, and reports that display data and insights.
- AI-Powered: Looker has enhanced its data visualization skills by tapping the power of DuetAI. It brings an intelligent analyst to assist your organization’s data in creating advanced visualizations within a few sentences of instruction. Moreover, it also utilizes natural language to create formulas.
- Extensive Collaboration: Looker has many third-party network ecosystems to strengthen your extensive data visualization process. You can embed data from Looker’s BI software with tools such as Confluence, Salesforce, and PowerPoint.
How can Airbyte Help You Enhance Big Data Visualization?
Using the above-listed big data visualization tools, you can efficiently draw data-driven insights and make faster organizational decisions. However, you need to unify your data and streamline information to harness the power of data. Airbyte is a reliable platform that effortlessly manages large datasets if you want to create robust data integration with automated data pipelines to consolidate the data.
With its extensive portfolio of over 350+ pre-built connectors, Airbyte can help you streamline data extraction and replication by facilitating data transfer between multiple sources and destinations. Airbyte can also assist you in seamlessly building custom connectors through its no-code Connector Development Kit. Using its user-friendly interface and no-code methodology, you can extract and organize structured and unstructured data from different sources.
Once you have created a single source of truth, you can connect your big data visualization tools to analyze data and quickly make informed decisions.
Final Word
As data expands in size and complexity, big data visualization tools will become more imperative than ever. These tools provide a comprehensive and updated set of features to represent a large volume of complex data in a clean and interactive visual. This article covers some of the best visualization tools for big data that you can utilize to perform big data analytics and transition your business ideas into successful projects.
We recommend using Airbyte to simplify your big data visualization process and increase your business productivity. Sign up for Airbyte today to leverage its data integration capabilities for reliable and adaptable data visualization.
What should you do next?
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Frequently Asked Questions
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: set it up as a source, choose a destination among 50 available off the shelf, and define which data you want to transfer and how frequently.
The most prominent ETL tools to extract data include: Airbyte, Fivetran, StitchData, Matillion, and Talend Data Integration. These ETL and ELT tools help in extracting data from various sources (APIs, databases, and more), transforming it efficiently, and loading it into a database, data warehouse or data lake, enhancing data management capabilities.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.