
Power BI is a cloud-based analytics tool that enables you to visualize any data using the unified, scalable platform for self-service and enterprise business intelligence
We have all dealt with the concept of collateral coverage, one way or another. For instance, I have to leave my ID card at a gas station if I accidentally forget my wallet at home. Believing that things will turn out OK is terrific, but it would be wise to ensure everybody meets their obligations and, in the end, it is essential that we all get what we wanted in the first place.
There is no consensus of where the data democratization process begins and where it ends. It is a complex strategy with many proposed steps for data democratization to drive businesses. Each and every organization is unique and should define its own democratization steps according to its own needs, challenges, risks.
In a world lead by data, an enormous amount of data is getting generated every second. We know by now that a data warehouse adds a significant value to an enterprise, helping to improve decision-making processes, but what about access to the raw data? By implementing data democratization, you enable everybody in the organization to take advantage of data-informed decisions.
World and business are changing rapidly, and analytics is changing too. I will not talk about technical terms that are very popular now – Data Lakes, unstructured data, real-time analytics, Data Science, artificial intelligence, and other nice things everyone is talking about in the last few years. Instead, I would like to emphasize the change from a process-driven economy to an event-driven economy and what it brings to the analytical landscape.
According to Bill Inmon – the father of the data warehouse, “a data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in
In the previous and first blog in this series, we have tried to answer the question: Why do we need Data Warehouse models? In this blog, I will focus on model architecture and continue the analogy that I have used in the first blog – how is building a house similar to building a successful Data Warehouse.
If you are in telco, retail, healthcare or any other business, this business is the field where you are strong. You are not a Data Warehouse Architect, and if you want to implement a Data Warehouse system, you need somebody experienced in that field and a blueprint that you will use as standard and guidance.
In the first two blogs in this series, we have tried to answer the questions Why do we need Data Warehouse models and What are
Delegating tasks is a complex process that requires knowledge and understanding from both sides. This rule applies to both business and leisure life; for example, you can use it in your child’s upbringing and the tasks and challenges you give him or her in a particular period of life.
Power BI is a cloud-based analytics tool that enables you to visualize any data using the unified, scalable platform for self-service and enterprise business intelligence
We have all dealt with the concept of collateral coverage, one way or another. For instance, I have to leave my ID card at a gas station if I accidentally forget my wallet at home. Believing that things will turn out OK is terrific, but it would be wise to ensure everybody meets their obligations and, in the end, it is essential that we all get what we wanted in the first place.
There is no consensus of where the data democratization process begins and where it ends. It is a complex strategy with many proposed steps for data democratization to drive businesses. Each and every organization is unique and should define its own democratization steps according to its own needs, challenges, risks.
In a world lead by data, an enormous amount of data is getting generated every second. We know by now that a data warehouse adds a significant value to an enterprise, helping to improve decision-making processes, but what about access to the raw data? By implementing data democratization, you enable everybody in the organization to take advantage of data-informed decisions.
World and business are changing rapidly, and analytics is changing too. I will not talk about technical terms that are very popular now – Data Lakes, unstructured data, real-time analytics, Data Science, artificial intelligence, and other nice things everyone is talking about in the last few years. Instead, I would like to emphasize the change from a process-driven economy to an event-driven economy and what it brings to the analytical landscape.
According to Bill Inmon – the father of the data warehouse, “a data warehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in
In the previous and first blog in this series, we have tried to answer the question: Why do we need Data Warehouse models? In this blog, I will focus on model architecture and continue the analogy that I have used in the first blog – how is building a house similar to building a successful Data Warehouse.
If you are in telco, retail, healthcare or any other business, this business is the field where you are strong. You are not a Data Warehouse Architect, and if you want to implement a Data Warehouse system, you need somebody experienced in that field and a blueprint that you will use as standard and guidance.
In the first two blogs in this series, we have tried to answer the questions Why do we need Data Warehouse models and What are
Delegating tasks is a complex process that requires knowledge and understanding from both sides. This rule applies to both business and leisure life; for example, you can use it in your child’s upbringing and the tasks and challenges you give him or her in a particular period of life.