An Excel expert who understands the business goals of a company can use the software to discover new insights and opportunities in the data. By leveraging the powerful data analysis and visualization tools available in Excel, such as pivot tables, charts, and graphs, an expert can explore and analyze the data in new ways, uncovering patterns and trends that would otherwise go unnoticed.

For example, an Excel expert working for a retail company may use pivot tables to analyze sales data by product category, store location, and time period. This can reveal trends such as which products are selling well in which stores or at what times of the year. This information can then be used to inform decisions about inventory management, marketing strategies, and store operations.

An Excel expert can also use advanced features such as macros and VBA to automate repetitive tasks and perform more complex data analysis. This can save time and improve the efficiency of the data analysis process, allowing the expert to focus on uncovering new insights and opportunities.

Additionally, an Excel expert who understands the business goals of a company can also create dashboards, reports and forecasting models that can help in decision making process. These tools can help in monitoring key performance indicators (KPIs) and other important metrics, allowing managers to quickly identify areas that need attention and make adjustments as needed.

In summary, an Excel expert who understands the business goals of a company can use the software to discover new things by leveraging its powerful data analysis and visualization tools, automating repetitive tasks, creating dashboards, reports and forecasting models and monitoring key performance indicators. This can help the company make data-driven decisions that drive growth and improve overall performance.

Creating a large number of reports and a uniform database is a key step in discovering new things through data analysis because it allows for a more complete and accurate view of the data. When data is collected and stored in a uniform format, it becomes easier to aggregate and compare across different reports, allowing for a more holistic view of the data. This can reveal patterns and insights that would otherwise be missed when looking at individual reports in isolation.

For example, let's say a business has data on customer demographics, purchase history, and website behavior. By creating a uniform database, the business can combine this data and create a single report that includes information on customer demographics, purchase history, and website behavior. This report can then be used to identify patterns and trends in customer behavior, such as which demographic groups are most likely to make a purchase and what website pages are most frequently visited.

By connecting a large number of reports and creating a uniform database, businesses can also improve the efficiency of the data analysis process. When data is stored in a consistent format, it is easier to automate the process of extracting and analyzing the data, reducing the amount of time and effort required to create reports. This allows data analysts to focus on uncovering new insights and opportunities rather than spending time on data cleaning and preparation.

Furthermore, by having a consistent database, businesses can also have a better understanding of the data lineage, this is the flow of data in an organization, and the data governance, the set of policies, rules, and standards that control the handling of the data. This can help in identifying the origin of data, its accuracy, and completeness, which can be useful in making data-driven decisions.

In conclusion, connecting a large number of reports and creating a uniform database can yield a business that discovers new things as a result of the investigation in the data. This is because it allows for a more complete and accurate view of the data, which can reveal patterns and insights that would otherwise be missed. Additionally, it improves the efficiency of the data analysis process and can help in understanding the data lineage and governance, which are essential to make data-driven decisions.

Investigating existing information and going back through reports to discover new things is a process that can happen relatively quickly, depending on the size and complexity of the data, and the tools and resources available to the data analyst.

With the advancement of technology, data analysis tools such as Excel, R, Python, and SQL have become more powerful and user-friendly, making it easier for analysts to quickly and efficiently analyze large amounts of data. Automation and machine learning are also becoming more prevalent, which can help to speed up the process of data analysis and uncover new insights and opportunities.

Additionally, with the use of cloud-based data storage and analysis platforms, businesses can now access and analyze data from any location and device, which can allow for real-time analysis and quick decision making.

However, it's important to keep in mind that the speed of data analysis also depends on the quality and completeness of the data. If the data is not stored in a consistent format or is missing important information, it can take longer to analyze and may not yield as many insights.

In summary, investigating existing information and going back through reports to discover new things can happen relatively quickly today, due to the advancements in technology and the availability of powerful data analysis tools and platforms. However, the speed of the process also depends on the quality and completeness of the data, and it might take longer if the data is not stored in a consistent format or is missing important information.

How it is recommended to work with experts in the field of data investigations
It is highly recommended to work with experts in the field of data investigations, as they possess the necessary skills and knowledge to effectively analyze and interpret data. They have the ability to uncover patterns, trends, and insights that would otherwise be missed by non-experts.

Experts in the field of data investigations have a strong background in statistics and data analysis techniques. They are skilled in using tools and software such as R, Python, and Excel to analyze large sets of data and can effectively communicate their findings to non-technical stakeholders. They also have knowledge of data visualization techniques and can create clear and informative charts and graphs to present their findings.

Furthermore, experts in data investigations can help in providing accurate and reliable predictions about future trends and patterns, which can be useful in decision making. They can also help in identifying potential areas for improvement or opportunities for growth, and providing clear and actionable recommendations based on the data analysis.

Moreover, data experts can also help in data governance, data lineage, and data quality. They can help in designing and maintaining data structures, data flows, data quality rules, and data security, which are essential for making data-driven decisions.

In summary, working with experts in the field of data investigations is highly recommended, as they possess the necessary skills and knowledge to effectively analyze and interpret data, uncovering patterns, trends, and insights that would otherwise be missed. They can also help in providing accurate and reliable predictions, identifying potential areas for improvement, providing clear and actionable recommendations, and ensuring data governance, data lineage, and data quality.