Which analytics platforms offer the most advanced data visualization features?

Tableau: Tableau offers highly dynamic dashboards with interactive features like filters, parameters, and drill-down capabilities. Users can create visually appealing and responsive dashboards that update in real-time as underlying data changes.

Having navigated both Tableau and Power BI, I've found them to be powerhouse solutions for dynamic dashboards. Tableau stands out for its user-friendly interface and robust customization, while Power BI's seamless integration with Microsoft tools offers real-time insights. Your decision hinges on factors like user preference, current tech infrastructure, and tailored use cases.

Personally to me, Power BI & IBM Cognos Analytics offer a variety of features and have an easy to use service. Common features in both Power BI and IBM Cognos Analytics include advanced data visualization, self-service analytics, reporting, collaboration, integration with various data sources, and mobile access. They offer tools for data preparation, predictive analytics, and empower users with comprehensive insights for decision-making across the organization.

In my experience, I have found Tableau Dynamic Dashboards to be an excellent way to easily communicate and review information. Tableau is also much more creator friendly platform, allowing more individuals the power to create dynamic dashboards to share information themselves vs having to rely on a special team to do it for them.

Personally, Tableau is a great tool for data visualizations, very dynamic in functionality and can allow the user to great some great interactive dashboards with real time data. This probably allows it to trump over Power BI which is easier to use, has a massive advantage to organizations cost wise, and is completely integrated with the Microsoft suite of tools. Visualization wise, it does tend to have certain visuals/capabilities missing which Tableau just seems to do better. For the beginner, Power BI remains easily accesible and more user friendly

In my experience, PowerBI has a wide range of custom visuals that help address a number of business requirements. Having the power of M and Power Query along with the custom visuals such as calendar pickers, multi-info KPI cards, waterfall charts help understand data context very well. A feature that could be improved here is to make it mandatory for all custom visuals to be PBI certified, since exports are not supported for all custom visuals, limiting their use across the business.

In my usage of different BI tools, Power BI had the best variety of custom visuals available at there marketplace. The plug-in is simple and you don’t need any expertise to use advance visuals. Power BI makes it easy to plot visuals like Histogram, multi-level KPI cards, advanced cross tabs etc., at a single click.

Having used both Tableau and Power BI extensively, I prefer the Tableau over Power BI when it comes to customisation options which allows for more nuanced and tailored data exploration. Tableau offers a higher degree of control over the visualisation process, empowering users to create truly unique and personalised reports.

Every platform has its customization limitations and techniques to what level of custom visuals you're trying to achieve, and specific to the use-case. There is not one single tool or platform, which would completely meet your vision, but there are many possibilities to leverage, reference visualization libraries for your data visualization needs. Some of the key focus areas for customization: # Understand the audience or a persona # Define and design the right base template # Effective use of screen space / real-estate # Choose the right global color palette # Balance your overall story with good visuals / iconography / typography # Choose the right set of visualization for your KPIs / metrics # Keep it simple, engaging, and actionable

Microsoft Power BI: Power BI allows users to create custom visuals using its open framework, allowing for endless possibilities in visualization customization. Additionally, Power BI offers a marketplace where users can access a wide range of custom visuals created by the community.

Both Power BI and Tableau offer support for a wide range of data sources through connectors or alternatives, such as ODBC and OData. Power BI releases monthly updates that add support for new data sources, so it's worth checking their monthly updates blog for more details. I believe there is a need for both Power BI and Tableau to make it easier to connect to APIs.

"An analytics platform's ability to integrate is what makes it strong. Sophisticated systems can interact with a wide range of data sources, such as spreadsheets, cloud services, and databases, with ease. This pulls data from multiple sources to enable consistent visualization. In order to ensure accessibility where it is required, integration also includes sharing across platforms and embedding images into programs."

The effectiveness of an analytics platform hinges on its capacity to integrate with diverse data sources seamlessly. Cutting-edge platforms facilitate effortless integration with databases, cloud services, and spreadsheets, enabling users to consolidate data from disparate sources into cohesive visualizations. Moreover, these integration capabilities extend to embedding visuals into other applications or sharing them across platforms, ensuring accessibility and usability wherever your data is required. This robust integration empowers users to harness the full potential of data visualization by consolidating information from various sources into actionable insights.

Power BI can be really “power”ful in Azure Environment. Since it being a part of MS ecosystem, you can have access to every MS product/service to share and collaborate the data. For example, in the cases of performing ETL reporting , one can easily extract the data from the source, inject into ADL, script using python/pyspark, join using SQL, segment using Databricks, store the PII in Synapse and create the reports and visuals easily in powerBI by automating.

The strength of an analytics platform lies in its ability to integrate with multiple data sources, including databases, cloud services, and spreadsheets. This allows for a unified view of data from various places, and the capability to embed or share visualizations across platforms, making data accessible where it's most needed.

Tableau has been the go to tool for me on not just the visualisation but also to meet some analytical needs. The desktop version is handy in handling high volume data. Quick analysis can be done easily in Tableau. Also, the story feature, data blend features, ease of publishing etc are something to go for.

Tableau excels in a collaboration centered around data visualizations, offering features like commenting on visuals, version control, and robust data governance for controlled sharing. Its focus on visual collaboration fosters seamless teamwork on analytical insights. Conversely, Power BI's collaboration strengths stem from its Microsoft ecosystem integration. Users can leverage familiar Office 365 tools, enabling a unified experience. Additionally, its mobile capabilities and content packaging allow for broad distribution. The choice depends on whether your priority is fostering in-depth discussions around visuals (favoring Tableau) or collaboration within the Microsoft stack and broad content dissemination (favoring Power BI).

Google Data Studio: Google Data Studio offers strong collaboration features, allowing multiple users to simultaneously edit and view reports in real-time. Users can share interactive dashboards and reports with colleagues, clients, or stakeholders, and collaborate on data analysis and visualization projects.

In today's interconnected work environment, collaboration is paramount. Cutting-edge analytics platforms foster collaboration by enabling multiple users to collaborate on the same visualization simultaneously. Users can easily share their visualizations with colleagues, gather feedback, and implement changes in real time. This collaborative approach accelerates the data analysis process while ensuring that insights are effectively shared and leveraged across the organization. Through seamless collaboration, these platforms enhance the utilization of data visualization tools, facilitating efficient teamwork and informed decision-making.

Both Tableau and Power BI offer robust collaboration features, including web editing, commenting, and alerts. While Power BI offers powerful on-the-fly semantic layer changes, Tableau provides more granular control over user permissions, enabling fine-tuned content sharing.

Various Analytics platforms are offering advanced analytics capabilities. Some of the leaders are Oracle Analytics, Microsoft Power BI, Salesforce Tableau based on multiple analyst’s reports from IDC, Forrester and others. Oracle Analytics, as an example, is offering 1-click Forecast with ETS/ARIMA algorithms, AutoML, ML cluster and outlier, Auto-Insight, GenAI Assistant generating data visualizations using LLM on Datasets, Explain and Ask Data, Natural Language Query and Generation, AI vision, AI language, AI Document Understanding, Auto-segmentation, Spatial Analytics. All these features enable users to transition from descriptive reporting to augmented analytics and finally, to go from data to insights to decision intelligence.

Power BI has modeling capability which enables data transformation and data modeling for rich analytics. On top of that, Python and R integration makes it even better for advance analytics.

I've been working on forecasting revenue using Excel (Data > Data analysis >Regression), and I've found some useful time series analysis models for it: 1. Moving Average: This is like taking an average of revenue over a certain period to see the trend more clearly. 2. Exponential Smoothing: It's a way of giving more weight to recent revenue data, so the forecast reflects recent trends more accurately. 3. Linear Forecasting: This method predicts revenue based on a straight-line trend. 4. Trend & Seasonality Analysis: This involves identifying patterns over time, like if revenue tends to go up or down during certain seasons or trends. It helps in making more accurate forecasts by considering these fluctuations.

Enquanto especialista na plataforma Qlik, não poderia deixar de mencionar o poder de análise avançada do Qlik Saas. Além da fácil contrução de paineis interativos, a conexão com uma enorme quantidade de fontes diversas de dados, a Qlik avança fortemente na análise guiada por IA, Insight Advisor, aprendizado de máquina com o AutoML e muito mais.

Both Power BI and Tableau offer advanced analytics capabilities. Although Power BI provides an in-built AI capabilities like predictive modeling which can allow for a more in depth insights from data. Tableau thought its integration capabilities can connect to some advanced analytics tools like Python and SPSS to derive good insights and make data driven decisions across a wide range of industries.

When it comes to mobile accessibility, from what I've experienced, I really like Microsoft's Power BI. The development of applications is very easy to do on a desktop and then can be easily scaled for access via mobile or tablet. Once again, based on my experience so far, Power BI is undoubtedly my go-to choice in this regard.

Accessing dashboards on mobile has become easier with support for mobile apps in both Power BI and Tableau. Power BI's recent update (as of March 24) allowing for auto creation of dashboards has given it an edge over Tableau.

In today's mobile-centric landscape, having access to data anytime, anywhere is no longer a luxury but a requirement. Leading analytics platforms prioritize mobile accessibility, featuring responsive designs and user-friendly interfaces tailored for touch screens. Whether you're on-site or on the move, you can effortlessly view your data visualizations across various devices. This ensures that critical insights are always at your fingertips, empowering you to stay connected and informed, even when away from your desk.

Top-tier analytics platforms are designed with mobile users in mind, offering responsive design and touch-friendly interfaces. Whether you're in the field or away from your desk, you can access your data visualizations from any device, ensuring that you're never out of touch with the insights you need to drive your work forward.

I mostly use the desktop version of Microsoft Power BI and Tableau but I think Mobile version of Power BI is also great, specifically field work force and executive when they are away from their desk, it's really useful, Monitoring on the go is great.

Every analytics platform (especially proprietary) is built using at least demand and supply analysis, so features of them are somewhat similar. So an answer to the "Which analytics platforms offer the most advanced data visualization features?" question will be maximally subjective.

When choosing any analytics tool, there's often a learning curve involved, especially when considering custom visualization and collaboration features. However, integrating automatic suggestions or user prompts for visualization can streamline this transition, enhancing comprehension of data, facilitating forecasting, and adding significant value to the process.

Variety of Visualizations: Especially for personal usage, Flourish Studio serves a wide variety of visualizations. A further benefit of the platform lies in its ability to preview the type of chart each visualization will generate by using a sample data set. This feature enables users to conceptualize the nature of the data they wish to visualize and the configuration options available. Consequently, I regard it as an invaluable tool for aspiring data analysts eager to master data visualization techniques.

Ease of Use: Evaluate the platform's user interface, ease of use, and learning curve to ensure that users can quickly adopt and leverage its advanced features. Scalability: Assess the platform's scalability and performance capabilities to handle large volumes of data and support growing user demands. Pricing: Consider the pricing structure, licensing options, and total cost of ownership to ensure that the chosen platform aligns with your budget and business requirements.

Power BI is hands down one of the best (if not the best) dashboarding tools. Here's why: - Super user friendly: it's mind bogglingly easy to create a basic dashboard on power bi. Once you are done setting up your measures (you need to create a measure for each number you show on the dashboard), and relationships, it's simply plug play. - Attractive user interface. - Conducive with tabular visualization: I've not seen any dashboard that's as Conducive with tabular visualizations that power bi. This is super valuable for finance professionals.