What are the best BI tools to identify areas for process improvement?

BI tools that I’ve used to identify areas of improvement are data visualization such as Tableau and PowerBI. These tools allow me to visualize data to discover patterns that I wouldn’t have otherwise seen. Then I turn it into an unbiased story to provide actionable insight to the business. Also, doing data discovery and descriptive statistics using SQL, R, or Python how also helped me identify areas of improvement. And look at it over time to identify changes. Additionally, simply conversing with the business and field has helped me pinpoint what to look for in the data have helped me as well. Those are some of the tools that I’ve used in the past.

Utilizando ferramentas de BI e integra??o de dados, como Power BI, Tableau e outras, é possível identificar melhorias na integra??o de dados e otimizar os processos. O primeiro passo consiste em integrar dados provenientes de diversas fontes, como bancos de dados, planilhas, servi?os web e plataformas em nuvem. Essa integra??o permite combinar e consolidar dados de diferentes sistemas e formatos, garantindo sua qualidade, consistência e precis?o. Ao obter uma vis?o unificada e precisa das informa??es, torna-se mais fácil identificar áreas de aprimoramento na integra??o de dados. Por meio das ferramentas de BI, é possível realizar análises avan?adas e visualiza??es intuitivas dos dados, identificando gargalos, inconsistências e oportunidades

Actually all the steps and tools listed are good when the process is well defined and it captures the data as each process step is executed. Once the data is captured by an application then you can follow steps 1 through 5. However majority of times I have seen that the process itself is not well defined so it does not capture the right data or the quality of data is not good. The data quality issues should lead to a feed back loop where the process is reengineered to ensure right quality data is captured. The process improvement in this case follows classic change management with focus on people and culture.

The best BI tools for identifying process improvement areas depend on specific needs, but popular options include Tableau, Power BI, QlikView, and Looker. These tools offer data visualization, analysis, and reporting capabilities to uncover inefficiencies and enhance decision-making. Evaluate based on your organization's requirements and compatibility with existing systems.

Depende basicamente das necessidades, mas você tem o Kafka com Debezium para sincronizar dados e salvar em diferente sinks. N?o existe uma receita de bolo que funcione para todos os cenários, mas basicamente você precisa conhecer muito bem as fontes de dados, precisa reconhecer padr?es, você precisa garantir que os dados s?o íntegros e que gerem informa??es concisas. Muitas empresas trabalham com dados manuais, o que acarreta redundancia de dados, e por muitas vezes precisa linkar o dados original pelo que será substituído. Ent?o independente de ferramenta, antes você precisa conhecer muito bem as fontes de dados.

There is always a hidden secret behind data which can only be discovered once you analyse it. The first thing in any data analysis is your questions like, what is the purpose? What do you want to achieve? And why are you analysing it? Etc . Once you get the answer to your questions then you are good to go. There are various techniques to analyse data like identify patterns, trends, and useful insights which can help you business and eventually help you in the decision making. There are various tools but the most basic and user friendly tool is power Bi (in my opinion) which can actually do a lot of things for you.

In my experience Power BI is a top choice and can help for advanced data analysis features. These could include predictive analytics, trend analysis, and the ability to perform complex queries. Tools that offer machine learning capabilities can be particularly valuable, as they can identify patterns and correlations that might not be immediately apparent.

Data analysis is the beacon that illuminates the path from information to insight. Muhammad Tariq Rasheed rightly points to the 'hidden secret' in data, which is unraveled through thoughtful analysis guided by clear objectives. Ioannis Ioannou's preference for Power BI underscores the demand for tools that not only slice through data but also offer predictive and advanced analytics. It's through such tools, along with methodologies like machine learning and AI, that data transforms into strategic foresight, driving informed decision-making.

AI brings tremendous facilitation and advancements in data analysis. At the same time, it tempts one to consume the results without personal evaluation. I am a big fan and have had very good experiences with regular data analysis workshops, with an intelligent blend of business and analysts.

Effective process improvement begins with insightful data analysis ??. Several Business Intelligence (BI) tools excel in identifying areas for enhancement. Power BI is a top choice, offering intuitive dashboards and real-time analytics to pinpoint bottlenecks or inefficiencies ??. Tableau is another powerhouse, providing visually appealing data visualizations for a clear understanding of complex processes ??. For advanced users, Python with libraries like Pandas and Matplotlib can perform in-depth data analysis and create customized reports ??. No matter the tool, the key is leveraging data to uncover opportunities for optimization, ensuring your business runs smoother than ever ??.

While data visualization tools like Tableau, Power BI, and Qlik are undoubtedly powerful, they often give a false sense of simplicity. Just because you can make complex dashboards and graphs, doesn't mean you're communicating effectively. The real challenge is not in using these tools to create flashy visuals but in ensuring that the story you're telling with your data is accurate, clear, and devoid of misinterpretation. Sometimes, a simple bar chart in a basic program can be more effective than an interactive dashboard that requires a manual to understand. It's crucial to remember that data visualization is a means to an end, not the end itself. Remember my friend - The goal is insight, not just visual appeal. Is this true for you?

Process mining is a set of techniques for the analysis of operational processes based on event logs extracted from company’s databases, information systems, or business management software such as enterprise resource planning (ERP), customer relationship management (CRM), electronic health records (EHR), etc. In simple words, it’s about finding out how the processes are actually performed to discover problems and areas for improvement. Some examples of process mining platforms are Celonis, Minit, and QPR.

Power BI von Microsoft zeichnet sich durch seine Integration in das Microsoft-?kosystem aus und bietet intuitive Dashboards und Echtzeit-Updates. Es eignet sich besonders für Nutzer, die bereits mit Microsoft-Anwendungen vertraut sind. Tableau hingegen erm?glicht hochgradig personalisierte und komplexe Visualisierungen, ideal für detaillierte Datenanalysen. Seine Benutzeroberfl?che ist benutzerfreundlich und unterstützt umfangreiche Customization. W?hrend Power BI für seine einfache Integration und Benutzerfreundlichkeit bekannt ist, bietet Tableau fortschrittliche Visualisierungsfunktionen. Beide Tools sind mobilf?hig und ihre Wahl h?ngt von den spezifischen Bedürfnissen und der IT-Infrastruktur des Unternehmens ab.

Data visualization is a key aspect of Business Intelligence (BI) tools, serving as the visual storyteller of organizational data. ?? Tools like Tableau, Power BI, and Qlik provide dynamic charts and graphs that transform raw data into actionable insights. ?? These tools allow users to easily identify bottlenecks, inefficiencies, and trends within processes, making the complex data more digestible. The interactive dashboards enable stakeholders to explore data intuitively, fostering a deeper understanding of the areas that need improvement. ???♂? With colorful visuals and user-friendly interfaces, these BI tools empower organizations to enhance decision-making processes and streamline operations. ??

Effective visualization capabilities are essential. The best BI tools such as Power BI and Tableau offer interactive dashboards and customizable reports that make it easier to understand complex data sets. Good visualization helps in quickly identifying areas that need improvement and help in decision making

Data collaboration is the secret sauce ?? in the recipe for successful process improvement, and several Business Intelligence (BI) tools excel in this realm. These tools, such as Tableau and Power BI, act as data maestros ??, orchestrating a symphony of information from various sources. They enable teams to collaborate seamlessly, breaking down silos and fostering a culture of shared insights. With intuitive dashboards and interactive visualizations, these BI tools transform raw data into a masterpiece ?? that everyone can understand. By promoting collaboration, these tools empower organizations to identify bottlenecks, streamline workflows, and ultimately enhance their processes. ??

Datenzusammenarbeit ist für moderne Unternehmen unerl?sslich. Tools wie Alteryx, Domo und Sisense vereinfachen diesen Prozess. Alteryx bietet starke Datenbereinigungs- und Integrationsfunktionen mit Rollen- und Berechtigungsmanagement. Domo hingegen unterstützt Echtzeit-Dateneinblicke und -kollaboration, ideal für schnelle Entscheidungsfindung. Sisense erm?glicht interaktive Datenvisualisierungen und f?rdert Teamkollaboration. Diese Tools verbessern die gemeinsame Nutzung von Daten, erleichtern die Kommunikation zwischen Teams und integrieren sich nahtlos in bestehende Gesch?ftsprozesse, was zu effizienteren und datengesteuerten Entscheidungen führt.

Nach mitlerweile fast 8 Jahren Data Analytics mit Power BI, Tableau, R, Qlik ist und bleibt der wichtigste Aspekt die Wiederholung. Man darf einfach nicht an Schulungen, Repetition und spannenden Umsetzungsprojekten bei den Mitarbeitern sparen. Kontinuierliche relevante Anwendung ist das A und O, denn die Programme entwickeln sich so rasant und effizient weiter, dass man nie ausgelernt hat. Investieren Sie in Mitarbeiter Schulungen und in "coole" Umsetzungsprojekte innerhalb der Firma und lassen Sie nicht alles extern basteln, sondern vertrauen Sie Ihrem Team!

Creo que las mejores herramientas son el sentido común y hacer las cosas poco a poco. El sentido común para ver los procesos claves de la compa?ía y tomar la decisión de cambiarlos si es necesario. Hacer las cosas poco porque no se pueden analizar todos los procesos clave a la vez y no se pueden cambiar de forma simultanea. Dos aspectos más muy importantes: “Garbage in garbage out”, si los datos no son fiables o no tienen información que sirva para tomar decisiones se va tirar el dinero y hay que construir un sistema que sirva para ver la evolución en el tiempo. Tema herramientas: las de Data Mining aportan un valor increíble. Yo he trabajado con Celonis que me encanta pero hay otras muchas.

Scalability and Performance: Ensure that the BI tool can handle the volume of data your organization generates and can scale as your data needs grow. User-Friendliness: Choose tools that are intuitive and easy to use. This ensures that team members can use them effectively, regardless of their technical expertise. Customization: The ability to customize the tool to fit your specific needs is important. This includes custom reports, dashboards, and data fields. Integration with Existing Systems: The tool should integrate well with your existing technology stack to avoid silos of information. Security and Compliance: Ensure that the BI tool complies with relevant data security and privacy regulations.

La herramienta a utilizar debe ser transparente al volumen de datos a utilizar. El entorno ayuda mucho a la selección del producto, por la experiencia y el personal que se requiera. Al final el dise?o de tu BI es lo que predomina, puedes optar por probar con algunas herramientas y quedarte con la que mas te sientas cómodo.

The question here really is what BI tools will help in process improvement. There are Process Mining tools available in the market to address this specific need. These tools will help you identify the process followed in the systems by the business users based on specific actions and events followed and based on data at hand. The popular tools under process mining category are Celonis EMS, IBM process mining, UiPath, SOROCO Scout Platform. These tools help in providing visual representation of how the processes are designed vs followed in reality so that the processes can be improved. These are great tools and I personally had experienced the power of these tools and the insights are great to look at.