What is Business Intelligence?
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Analytics and Business Intelligence platforms allow you to organize your data into easy-to-understand dashboards and allows you to convert to reports.
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As Vera Technology we are always here for you when you need assistance about data management , business intelligence and data analytics.
A data warehouse, unlike classical databases, is a relational database designed to be used for querying and analysis. DWH system forms the basis of the business intelligence system.
It includes collecting and managing data from different sources in order to obtain structure data sets from unstructure data, and to make predictions.
As Vera Technology, we offer solutions to your company’s needs to reduce query traffic in operational systems, get faster answers from analytical queries, access data from different sources using a single platform and distinguish the right data.
Data Warehouse Model is created by collecting data from source systems within the organization (relational database, xls-txt files, unstructured data (social media), external source data, etc.) and transforming them in accordance with the data warehouse model; loading the model. In addition, within the scope of Data Quality, detecting dirty records, producing solutions with data normalization and/or identifying improvement points for processes within the organization.
Data Warehouse Model is created by collecting data from source systems within the organization (relational database, xls-txt files, unstructured data (social media), external source data, etc.) and transforming them in accordance with the data warehouse model; loading the model. In addition, within the scope of Data Quality, detecting dirty records, producing solutions with data normalization and/or identifying improvement points for processes within the organization.
Data Warehouse Model is created by collecting data from source systems within the organization (relational database, xls-txt files, unstructured data (social media), external source data, etc.) and transforming them in accordance with the data warehouse model; loading the model. In addition, within the scope of Data Quality, detecting dirty records, producing solutions with data normalization and/or identifying improvement points for processes within the organization.
Creating a Data Warehouse Model: Designing the Data Warehouse Model according to the definitions (Formula & Exceptions) specified in the Corporate Data Dictionary. Determining the method to be applied according to the needs of the 3NF Modeling, Star Schema Modeling, Snow Flake Modeling versions, taking into account the organizational needs.
Definition of Corporate Data Dictionary: Making and documenting the definitions of all metrics and breakdowns (KPI & Dimensions) used and required to be used in the organization. In addition, the implementation of the Data Culture operation within the organization through the Data Steward information of the definitions made.
Data Warehouse Model is created by collecting data from source systems within the organization (relational database, xls-txt files, unstructured data (social media), external source data, etc.) and transforming them in accordance with the data warehouse model; loading the model. In addition, within the scope of Data Quality, detecting dirty records, producing solutions with data normalization and/or identifying improvement points for processes within the organization.
Modeling all data (Internal and External) in the institution in the Datawarehouse environment by integrating Facilitate historical, enterprise-wide Dimension-based reporting and data analysis Ensuring that all in-house employees can access the same data at the same speed over the same environment Integration of data from internal or external environments into the Data Warehouse in desired periods (instant-daily) (ETL)
Review and documentation of sets for the institution Design of Senior Management Reports and Department Reports With an easy Data Warehouse model, each invoice is self-prepared within the organization.