Hier erfahren Sie, wie Sie Daten und Analysen nutzen können, um Ihre Geschäftsentscheidungen zu treffen.

Other reasons to integrate data from transactional applications and other disparate sources is so that you can use one language internally as a data team. Most systems use different databases. This means that if you don’t integrate into a data warehouse or data lake then you would need to use different SQL dialects or even other programming languages to analyze data. Integration allows you to use one language to analyze the data after ingestion.

Business should aim at integrating data concepts especially from various sources to aid in making informed decisions that benefits the business. In order to achieve a maximum profits,they have to make use of the data available to them to get insights that will make them thrive.

A solid data integration is essential in developing analyses at all levels in a company. If the data that a company consumes is not integrated or even integrated but not accurate, you may find yourself with gaps of information that will negatively impact your business. One good example that I have experienced is by having the board of a business presenting a report to stakeholders where the information is distorted due to the lack of precision of the data integration. Having a unified and consolidated repository of data is the basis of having a precise and efficient data set in order to identify trends and establish strategies at all levels in a business.

A integração de dados sempre começa com o entendimento das fontes que você ira cruzar, como elas se correlacionam? ela se correlacionara por completo ou só em uma partes de dados? é importante lembrar de adicionar mesmo não se correlacionando o N/A para nunca deixar gaps de entendimento do usuário pois eles sempre vão querer no maior nível de detalhe. e ficara a duvida :Se o campo existe porque ele não se cruza?

This is a simplified example, but it illustrates how a business can use data and analytics to inform decisions and improve outcomes. An online retailer wants to boost sales and customer satisfaction. They collect and analyze data on sales, customer behavior, and feedback. Insights show high sales on weekends, a product with high returns, and the effectiveness of follow-up emails. They decide to run weekend promotions, check the problematic product, and start an email campaign. They monitor the results, leading to increased sales and customer satisfaction. This shows how data can guide business decisions.

Estoy de acuerdo con la afirmación sobre la integración de datos. Consolidar información de ventas, interacciones con clientes y operaciones en un solo repositorio es esencial para obtener una visión integral del negocio. Automatizar este proceso con herramientas avanzadas asegura datos precisos y actualizados, fundamentales para mantenerse competitivo. Un conjunto de datos unificado permite identificar patrones y correlaciones, potenciando la analítica y la toma de decisiones estratégicas. Invertir en integración de datos transforma la forma en que una empresa comprende y utiliza sus datos.

Para além dos benefícios tecnológicos, vale citar o aumento de produtividade e a mitigação de erros como vantagens da integração de dados. No setor em que atuei por um tempo, sempre que precisávamos de dados, tínhamos que exportar planilhas manualmente de diferentes bases, realizar um pré-tratamento, integrá-las e, só então, trabalhar com as informações. Em um ambiente de dados integrados, essas etapas não são necessárias. Isso permite agilizar o processo de construção de inteligência e evitar possíveis erros humanos durante o pré-tratamento dos dados.

Data is a critical asset for any company, driving informed decision-making and strategic planning. It provides actionable insights into customer behavior, market trends, and operational efficiency, enabling businesses to identify opportunities and mitigate risks. By analyzing data, companies can optimize processes, reduce costs, and enhance product or service offerings, leading to improved customer satisfaction and increased revenue.

A ferramenta de analise, para o cientista de dados, sempre vão ser as mais sofisticadas e atualizadas, mas o usuário não ira ter acesso a essas ferramentas como você tem, eles vão querer baixar para o Excel bruto para fazer as suas analises se você não disponibilizar o que ele necessita, então o Excel é a ferramenta de análise do dia-dia.

There are many data analytics tools which can be adapted in various business settings that will facilitate easy analysis of business data to gain insights. Tools like excel, R, Python and and visualization tools like Tableau and Power Bi when used efficiently they will help provide clear findings to foster growth of the particular business under consideration.

Dependendo da complexidade do projeto, eu diria que a ferramenta usada na análise de dados realmente impacta na qualidade dos resultados. No entanto, vale lembrar do ditado "menos é mais". Nas atividades do dia a dia, geralmente, não preciso de ferramentas com funcionalidades muito sofisticadas. O Excel, o Power Query e a linguagem Python, na maioria dos casos, cumprem com excelência os seus papéis.

Em minha experiência a cultura orientada por dados é por onde se deve começar, tal cultura deve ser implantada na empresa antes do início da construção de painéis. De nada adianta dados e painéis se a cultura da empresa é baseada na mera opinião dos colaboradores.

Desde mi experiencia, la falta de una cultura basada en datos es uno de los mayores obstáculos para una toma de decisiones efectiva. Aunque fomentar esta cultura es vital, muchas organizaciones aún no entienden la importancia de capacitar a sus equipos para interpretar y utilizar los datos correctamente. Sin esta base, confiar en la analítica se vuelve difícil y las decisiones pueden ser menos informadas. Es fundamental que las empresas inviertan en formación continua y promuevan una mentalidad de datos en todos los niveles. Sin una cultura sólida, los esfuerzos en analítica no alcanzarán su máximo potencial y la calidad de las decisiones empresariales sufrirá.

Predictive analytics provides businesses with clear view of market trends and customer preferences, enabling informed decision-making. It optimizes operations by forecasting demand and efficiently managing resources, leading to cost reductions. Early identification of risks and understanding customer needs allows businesses to proactively enhance customer satisfaction and loyalty. Ultimately, predictive analytics leverages data to achieve significant business outcomes.

"A Picture is worth a Thousand Words"; this adage goes really well for a Dashboard. A dashboard is at the heart of Decision-making process for business executives. KPIs displayed on the Dashboard help business teams keep a track of the performance of key drivers. Wjere I have seen this simple combination of KPIs and Dashboards go wrong is, when we start including all business metrics as KPIs. Business teams should carefully select the business metrcis that qualify as KPIs and wherever possible should also include both Lag and Lead Indicators as KPIs on Dashboards. Keeping a constant track of these Lead and Lag indicators can help businesses run their operations more effectively and avert few crisis situations before they take place.

KPIs are essential to your business. When I sit down with a customer (internal or external) one of the first questions I ask before building a dashboard is “what data and KPIs drive your business?” or “what do you want to see as soon as you open up your dashboard?” Having a dashboard to help monitor KPIs can help drive business and allow you and your leadership to make the best business decisions based off of data. When we started integrating Business Intelligence at our company we started with our largest division. As soon as the other divisions saw the opportunity and value of having a KPI dashboard, they all wanted one. Now each division at our company has access to their own dashboard to track KPIs and the impact has been amazing!

Yeah, the need for ethical consideration cannot be overemphasised in today’s work environment to ensure that available data are used with the right approval and that intellectual property is respected where necessary.

A medida que las empresas avanzan hacia una toma de decisiones basada en datos, es vital que la recopilación y el análisis de datos respeten las leyes de privacidad y las normas éticas. La transparencia en el uso de los datos de los clientes y la implementación de estrictas medidas de seguridad son fundamentales para mantener la confianza y la reputación. He observado que muchas organizaciones no prestan suficiente atención a estas consideraciones éticas, lo que puede resultar en consecuencias graves tanto para la empresa como para sus clientes. Las implicaciones éticas deben estar siempre en primer plano, ya que el impacto de ignorarlas puede ser devastador a largo plazo.

Proactive thinking is crucial to success acceptance of a decision making system. Data analytics system is technology based itself. Business leaders may lack of knowledge of technology. When building a data model for decision making system, the design process needs to be proactively focused on business objectives and beyond to provide what could be achieved further for the business ahead of what business leaders could ask more upon seeing the system.