This article will discuss a few guidelines for editing and designing dashboards. It may not always be possible to follow these guidelines since in some cases you might already have a specific design idea in mind for the dashboard you are designing.
In this article, we will start querying CSVs and JSONs in Google Cloud Storage (GCS) and create new tables from existing tables (ETL process). This article is mainly for BI Developers who want to expand their capabilities to handling Big Data and finished successfully part one.
In this article, we will start querying CSVs and JSONs in Google Cloud Storage (GCS) and create new tables from existing tables (ETL process). This article is mainly for BI Developers who want to expand their capabilities to handle Big Data and finished successfully part one.
In this article, we will start exploring AWS Athena, You will learn how to create a query. This article is mainly for BI developers who want to extend their capabilities to handle Big Data.
The Drill-through solution is beneficial for companies that would like to take their BI to the next level: A data-driven solution. We implement such solutions to deal with issues efficiently and create an impact on the company's performance.
In certain cases, our database is being connected to different data sources - eg: cloud, local files, CRM systems, etc. Usually, the number of data sources isn't a problem for designing the database. However, there are certain cases where the data we receive from the different sources isn't coherent and can lead to some issues regarding data integrity.
Data warehouse architecture is a broad and important concept that shapes the data structure of one’s organization. It has a large effect on an organization’s data-related aspects such as data flow process, development, and maintenance costs, reporting ability, etc. In this article, we are going to discuss two of the most common approaches for data warehouse architecture - the Kimball and Inman methods.
Are you a "Report Manager" or a "Dashboard Manager"? Everyone knows the difference between a report and a dashboard. Imagine looking at an extensive report with many columns, records, and much information. And in contrast - a dashboard with a few KPIs and a few graphs from which you can directly derive insights. Which will you choose when it comes to analyzing data? Does this indicate the type of manager you are?