Data Mess? Let Consolidation (ETL) Clean It Up

Published: Jul 20. 2023
Data Consolidation (ETL)

Some customers are capable and willing to cover projects in-house and use our expertise only for selected parts, this is usually the case of Data Consolidation or ETL process. This is a service or part of BI project, covering steps 2 to 4 as described in our 3rd blog post

“We will collect, combine, clean, and store your data from multiple sources and create a single point of truth for your best use.” 


What are we doing as part of this service? 

ETL Process 

⎯  Extract - we will collect data from multiple sources (SQL, Share-point, CSV, etc.) 

⎯  Transform - we will clean, deduplicate, validate, and explore the data 

⎯  Load - we will move data into the End target (DB, Data Warehouse, etc.) 


⎯  Data quality - we will improve data quality and integrity before its used in your operations 

⎯  Data analysis - we will provide actionable insights and forecasts   

⎯  Business planning - we will provide a complete picture of your entire operation 

Data Source | ETL | Data Warehouse | Touch4IT

What will you get?

⎯  Clear, clean, unified data with best practice principles 

⎯  Reusable data will save your time, space, resources, and finance 

⎯  Promoted, thus trusted datasets can be used by all departments (calendar, list of employees, customers, invoices, etc.) 

⎯  Streamline your processes 

⎯  Increased productivity by optimizing, and removing inefficient or redundant tasks 

⎯  Possibility to quantify processes, evaluate efficiency and identify potential improvements 

⎯  Lower costs with improved efficiency 

⎯  Unblocking bottlenecks 

⎯  Data consistency 

⎯  Integration through a unified view 

⎯  Validation through accuracy, completeness, and consistency 

⎯  Strict policies through data entry establishment and regular process reviews 

⎯  Data Silo Avoidance through best sharing possibilities 

⎯  Insights will be shared as a full picture and won't be gathered by different departments separately 

⎯  Single point of failure - data loss avoidance 

⎯  Not only one person has access as data are on shared space not only on the local machine 

Data Sources | Touch4IT image



Tomas Kavicky
Identification & Valuation Manager and a huge fan of Data Science, BI, MS Power Platform, and Six Sigma Principles,

Lukas Lani
Project Manager, technically based, open-thinking with strong analytical skills. 


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