Today, Business Intelligence and Reporting systems have become one of the most critical tools used by companies to manage their business.
The way to make strategic management is through the business plan and constantly monitoring this business plan. For this, Business Intelligence solutions built on robust systems are the right tool.
Another issue that has become indispensable today is Performance Management. Performance Management should be considered integrated with strategic planning and evaluated accordingly. For systems that can melt strategic plan, business plan, realization and performance management in a single pot, business intelligence software should be able to receive data from many sources and have the ability to transform this data into information.
Business Intelligence and Reporting Solutions Consulting, ETL & Data Integration Data Warehousing Business Analytics Performance Management Systems (KPI & Scorecards) Corporate Reporting Systems, Executive Reports (Dashboards, Cockpits), Data Mining ( Data Mining), Statistical Estimation and Modeling (Predictive Analysis).
Datageeks provides solutions and solutions for corporate customers in Turkey’s top 1000 list, and multinational companies in fields such as Business Intelligence (Business Intelligence – Qlik Sense – Qlikview), Machine Learning (Rapidminer), Advanced Analytics (Advanced Analytics) at home and abroad. offers services.
Applications developed with the right quality and technology provide great added value in companies where there are situations such as confidentiality, competitive advantage, and unique business processes.
Needs Determination, Requirements Determination Technology Selection Analysis & Design Development Test Implementation & Adaptation Maintenance & Continuous Improvement
We also provide professional business intelligence and reporting solutions consultancy at every stage in Qlik Sense, Qlikview, RapidMiner products.
The fact that an institution has quality data displays the character of a continuous discipline rather than a project that can be started and finished all at once. It is not possible to talk about the efficiency of business intelligence projects that an institution with low data quality is trying to implement by making large investments. Data quality solutions basically cover the software tools, methodology and processes required to make the data accumulated in the institution accurate, complete and consistent.
Today, every organization is aware that their data is more or less dirty. Data entries that are not made as standard, information is not entered in some fields, inconsistencies occur between tables in information entries involving more than one table, or double records/customer deduplication projects are situations where the need for data quality projects becomes evident. One of the expected results in data quality projects is to reduce data pollution as much as possible.
The starting point in improving data quality is through the Data Profiling phase. Data Profiling can be described as examining the data, finding errors, investigating the causes and effects of these errors, measuring the errors and presenting them in report and cockpit environments. With Data Profiling, it is possible to follow how full the fields in the database are numerically and in percentage, the breakdown of different values in the relevant field, or how high the percentage of data that is in one table but not in the other table is. Meanwhile, end users need to be able to give some rules. For example, “In a database, although there are 2 different fields such as Email1 and Email2, only 1 of them has an email address, this is correct data for me even if the other field is empty!” A user who can say should be able to define this rule himself. Such a user should be able to monitor data quality with proactive methods, periodically and with automated methods, and automatically send alerts when necessary. For example, such a warning can be implemented by sending an e-mail to the relevant persons if the institution’s Data Quality Score falls below a limit. Data Profiling software must be capable of being used by the business unit or departments in an organization that is responsible for the data and owns the data. This requires such software tools to have an interface that can be used by end users rather than IT.
