Data sharing has become an essential business capability, increasing the alignment of D&A strategies with enterprise goals. How to use data to accelerate digital transformation?
Change your mindset. Data sharing should be a business necessity so that data and analytics leaders will have access to the right data at the right time, enabling more robust data and analytics strategies that deliver business benefits.
Develop trust-based mechanisms that establish high levels of trust in the data source and separately in the trustworthiness of the data. That way you can align appropriate data use with your business goals, both within and outside your organization.
Distinguish your data management strategy between data warehouses, data lakes, and data hubs. Create new and flexible data management practices that adapt to uncertain and changing environments.
Need help with any of these areas? Let us know.
From building data warehouses to big data analytics to reporting. We are moving your business forward through BI.
IT solutions that help you make better strategic decisions, perform efficient maintenance, and ensure regulatory compliance.
For Linet Group, a leading global manufacturer of medical bed equipment, we built a Data Warehouse with financial and sales reporting that includes data from 17 systems and 15 countries, enabling the company to grow. Thanks to our expertise and custom tools we were able to come up with this solution in one year.
We have created a new unified interface that allows the retrieval of central Reference Data Management with the possibility of filtering, translating, and refining relational records of more than 1.300 code lists in 1 of 6 different environments and making it transparent, effective, and automatized.
We take care of the cleansing and standardization of personal data in Škoda AUTO systems and created a 'golden record' whilst maintaining the legal GDPR basis, the purpose of processing, and consent within an automated process.
Such a large-scale integration project is unprecedented in the history of Linet. Its complexity is comparable to the data integration of any large corporation. I am pleased to see the result of the joint work of all involved and that the foundations laid in the first phase will continue.
Chief Information Officer, LINET Group SE
We can help you become a data-driven company
Data Warehouse is the cornerstone of building a data platform for analyzing your data. All technologies change rapidly and data warehouses must be able to absorb the surrounding changes well. We have experience with different technologies (Microsoft SQL Server & Azure Data Factory, Databricks, Synapse & Power BI, IBM, Teradata, SAS, SAP), methodologies (banking, automotive & utility), and sector business models. We can build a data warehouse from the ground up, evolve your existing one, or move it from your infrastructure to the cloud (MS Azure & AWS).
Big Data allows you to use unstructured and vast amounts of data for analysis. We use Big Data techniques for Data Lakes, where even structured data is available faster and more efficiently than through a data warehouse. We can combine all this together to create the most efficient and flexible data platforms in a hybrid world of on-premise and the cloud using Microsoft SQL Server & Azure Data Factory, Databricks, Synapse, Data Lake Storage, Cosmo DB & Teradata & Cloudera & MapR / HPE Ezmeral.
Instant availability of data is essential for fast and continuous operational actions, decision-making, and risk management in business. A day or two of old data is simply not enough anymore to offer the right product to the client at the right time. Operational Data Store makes data from different systems available instantly using Microsoft Azure Data Factory, Databricks, Synapse, Data Lake Storage, Cosmo DB & SQL Server.
We bridge the worlds of data and business and pride ourselves on complementing technical expertise with superior business knowledge. This enables us to recommend not only the right kind of visualization but also the content to be displayed.
We deliver a methodical framework that helps keep data in good shape for the long term. Data quality can also be addressed with a technology platform for data quality management (Informatica Data Quality & SAS Data Quality). We can measure and continuously evaluate data quality.
Our team helps clients identify unique records (e.g. customers) in their databases and link them to relevant data in other systems. For starters, we can measure data quality and perform data profiling. Deduplication and cleansing of the existing database are also part of the optimal solution. We have extensive experience from both the banking world and government using SAS DataFlux & Informatica Customer 360.
If your codebooks are not uniform, or you are recording the same codebook multiple times with different content when they should be the same, then you are not managing your codebooks correctly. We can help you. We are experienced and we can deploy specialized solutions (Trask Reference Data Store / RDS & Informatica Reference 360) that will improve the quality of your codebooks, simplify your work and reduce costs.
Business Data Dictionary (BDD)
The data dictionary is used to record the content of the data warehouse, its inputs from source systems, and outputs within reporting. BDD shows the structure, content, origin, and ownership of data. It provides a view across the entire structure, greatly simplifies understanding data analysis, allows you to trace potential errors, and assists in change management.
Reference Data Store (RDS)
A tool for managing the content of codebooks across large IT infrastructures and multiple environments simultaneously. RDS validates, quality manages, unifies, stores, and distributes codebooks using built-in workflow, ownership concepts, setting time expirations for codebook content, event tracking, and task automation.
Talk to our experts on Data
Data and Client Director
Data Management Manager
Manager of Data Science