No matter what you want to analyze, the basis should always be a high-quality database.

Data Engineering

For valuable insights and reliable results, you need a database with consistent, up-to-date data and high data quality. Well-designed data technology enables you to efficiently process unstructured, complex, and ever-growing data from a variety of sources in both large batches and a continuous stream with low latency. By using Big Data technologies, data does not have to be altered or forced into a relational schema. They also enable cost-effective scaling of performance and storage, as well as rapid access to new and existing data sources.
Create cross-system and complex analyses as well as meaningful reports.

Big Data
Data Engineering


Central database

A central location for all data and the same reference through a uniform database enable a single source of truth. This makes key figures and analyses comparable throughout the company.

Uniform standards

Uniform standards ensure high data quality and data reliability. Thus, data of better quality can be made available for analyses and reports.

Increase efficiency

By building fast processing pipelines that can effectively analyze large volumes of structured and unstructured data sets. This enables analyses from different data source systems in the shortest possible time.

Simple integration

New data sources can be easily and flexibly integrated into the infrastructure and made accessible via interfaces.

Our Data Engineering Team
supports you with

Data preparation

Extract data from disparate sources such as databases, APIs, files, or external systems and review, validate, and clean the data to ensure it is consistent and complete.

Data modeling

Creation of data models that define the structure and relationship of your data. Databases and schemas are created for secure and performant access and storage of your data.

Data cleansing

This cleanses and transforms your data by correcting erroneous, incomplete or inconsistent data. Data validation helps to ensure that the data meets the defined quality standards.

Data integration

ETL processes extract, transform and load your data into the desired format. The data is thereby integrated from different data sources or data source systems into an analysis platform to create a uniform and integrated view of the data.

Data quality assurance

This ensures that your data is of high quality and meets the defined standards. Data profiling and data mining are used to identify and eliminate data anomalies or inconsistencies.

Data management

Management of databases and other storage media to ensure the integrity and security of data.

We support you in this!

Benefit from an
optimal Data Engineering

We support you in the data management process with optimal data engineering that captures your (raw) data from various source systems, puts it into a clean, structured, and usable form, and prepares it so that it is accessible for analysis, processing, and use in companies. It doesn't matter whether the data is unstructured, complex, consistent or constantly growing. We help you to prepare your data in such a way that data quality, data integrity and data consistency are guaranteed. In this way, you strengthen confidence in your data and create the data basis for reliable results and valuable insights.

TIQ Mitarbeiter Thomas
Thomas Weise

Senior Consultant Business Intelligence & Big Data

TIQ Solutions GmbH

Inspiration for your application

Success Stories

Big Data & Data Science

Big Data analytics and dashboarding for sentiment barometers with social listening

Data Science

Predictive maintenance in car body manufacture

Business Intelligence

Big Data for digital television and telephony at Deutsche Telekom

Data Quality

Data quality management in the chemical industry

Business Intelligence

Intelligent Controlling with QlikView® at the Karosseriewerke Dresden

Business Intelligence

Traceability of the semiconductor-production by building a Big Data database

We look forward to
your message!