Are you more of a Report or Dashboard Manager?Oded Weiss
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?
Kimball vs InmanYoav Shimonovich
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.
Moving from Data Warehouse to Data LakeBenji Nissim
this article will discuss the two methods of storing data - data warehouse and data lake, their differences and use cases.
Count Function Use CasesNoga Levy
The COUNT function in SQL, is a basic aggregate function that can be used in a variety of scenarios from basic to complex ones. in addition, Count can also be used as a window aggregates function.
Window Functions – Part OneYoav Shimonovich
Window functions are a set of functions that were introduced in 2003 and can be used to solve a variety of scenarios in analytics. Their big advantage over other methods is their great flexibility.
Dealing with Multiple Sources of InformationOded Weiss
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.
Beginners guide to BQ – Part 2: Query CSV & JSON filesBaruch Shteken
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.
Beginners guide to BQ – Part 1: Getting StartedBaruch Shteken
In this article, we will start exploring Google BigQuery. You will learn how to create a Project, Schema and a query. This article is mainly for BI Developers who want to expand their capabilities to handling Big Data.
A Beginners guide to Athena – Part 2: Query CSV & JSON filesBaruch Shteken
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.
Dashboard design in a nutshellAssaf Mazal Tov
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.
The drill-through solution from Power BI to PriorityDA Team
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.
Beginners guide to Athena – Part 1: Getting StartedBaruch Shteken
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.
Window Functions – Part TwoYoav Shimonovich
in the second part of the article, we are going to discuss analytical functions and how we can apply their unique functionality to help us solve various scenarios.