"Data as the New Currency: How Analytics is Transforming Modern Business"
March 1, 2023
Are you curious about how data analytics is transforming modern business?
Data has become the new currency and every company is striving to collect and analyze their data to make informed decisions for a better future. But with the huge amount of data stored in databases and excel sheets, making sense of it can be a daunting task.
In today's fast-paced and highly competitive business environment, data has emerged as a game-changer, a valuable asset that can be leveraged to gain a significant competitive advantage. As more and more businesses turn to digital technologies to streamline their operations and engage with customers, the amount of data generated on a daily basis is exploding. However, data is not valuable in its raw form. It needs to be properly collected, organized, and analyzed to reveal insights that can drive business success. In this blog, we'll delve into the critical role data plays in the modern business landscape and explore the techniques used for data preparation and report creation. So, let's dive in and discover the exciting world of data analytics together!
Data and its importance :
Data is an unorganized and raw collection of facts that has massive importance for a company. In the modern world, every company wants to collect and analyze their data to come to a certain conclusion in order to make informed decisions. It might help them to build a better future. It gets tough to make sense of the huge data stored into databases and excel sheets.
Our main objective working financial domain was to understand the business requirements from the clients, design and code the logic that acts as a data source, create and maintain meaningful and insightful reports which can be accessed and used so that organization can pinpoint and evaluate relationships, patterns and trends so they can glean insights and draw conclusions based on the data and use these to make informed decisions.
Prepping data and selecting data source for reports :
A data source is a place where information is obtained. The source can be a database, a flat file, an XML file, or any other format that a system can read. The input is recorded as a collection of records that contain information used in the business process. That information can include customer details, accounting figures, sales, logistics, and more.
Typically used data sources for the reports :
Direct query for Paginated Reports using SSRS(SQL Server Reporting Services) and Power BI. This can be achieved post establishing a connection to the server and the database you have access for. A direct query includes the logic required to collect the data from the tables deployed within the database according to the business requirement.
emp_id, emp_name, hire_date, salary
View is a virtual table based on the result-set of an SQL statement. A view contains rows and columns, just like a real table. The fields in a view are fields from one or more real tables in the database.
USE AdventureWorks2012 ;
CREATE VIEW HumanResources.EmployeeHireDate
SELECT p.FirstName, p.LastName, e.HireDate
FROM HumanResources.Employee AS e JOIN Person.Person AS p
ON e.BusinessEntityID = p.BusinessEntityID ;
Stored Procedure is a group of one or more pre-compiled SQL statements into a logical unit. It is stored as an object inside the database server. A stored procedure comprises of multiple parameters which can be used to take input value. Using stored procedure has multiple benefits like Reduced Traffic, Stronger Security, Reusable, Easy Maintenance, Improved Performance .
SELECT * FROM Customers WHERE City = @City
Data Cubes is an OLAP cube, also known as multidimensional cube or hypercube, is a data structure in SQL Server Analysis Services (SSAS) that is built, using OLAP databases, to allow near-instantaneous analysis of data. Data Cubes can be designed using SSDT (SQL Server Data tools). After establishing connection with the server and intended database, tables can either be directly imported or we can also write a direct query to get intended fields within the table. Post getting all the tables, relationship should be established within the tables logically. The ready data cube can then be deployed on the Analysis server and can be used a data source for the reports.
Report Creation :
The reports can be classified into 2 categories :
Paginated Reports : Paginated reports are designed to be printed or shared. They're called paginated because they're formatted to fit well on a page. They display all the data in a table, even if the table spans multiple pages. According to the needs of the clients, there are few reports where they might need to download heavy data through our reports in table format into the file type they want, SSRS has multiple import options so it was feasible to create tabular reports using SSRS tool.
Power BI Reports : A Power BI report is a multi-perspective view into a dataset, with visuals that represent findings and insights from that dataset. A report can have a single visual or many pages full of visuals. A good Power BI report comprised of user friendly options of adding multiple filters, easy to understand visuals and give complete information of the data residing within the database accurately.
Once the reports were made using the above tools, the next task was to deploy the reports on Power BI server and scheduling for regular refresh to get new data into the file. Ideal practice for the reports was to store data worth 2 years from the present date considering the report performance and smooth operation.
Refreshing data within the cubes is also necessary and scripts were written and deployed on the server.
By utilizing various data sources such as direct queries, views, stored procedures, and data cubes, companies can efficiently gather and prepare their data for analysis. With meaningful and insightful reports, businesses can evaluate relationships, patterns, and trends to gain valuable insights and make informed decisions that drive success.
In this blog, we explore the importance of data analytics in modern businesses. If you have similar requirements, Predera is here to help.
We hope you found our blog post informative. If you have any project inquiries or would like to discuss your data and analytics needs, please don't hesitate to contact us at email@example.com. We're here to help! Thank you for reading.
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