Data Consolidation & Migration

Here are some things to keep in mind when planning how to collect, store, and query the vast amount of data that your company uses every day.


Data Sources

Most companies maintain data in a variety of different formats: plain text, Excel spreadsheets, multiple SQL databases, etc. Within those SQL databases, different schemas and data relationships exist. And new data being received arrives in a number of different formats as well. When developing your data collection strategy, it's critical to understand the differences between these formats and how those differences may contribute to difficulties in presenting unified views of your data. For example, if you need two join web analytics data with call center data, you will experience difficulty unless there is a primary key that can be used to identify the same person in both data sets. Planning ahead for this need will eliminate problems such as this one when it comes time to query and present this data to the end users inside your company.

Data Formats

Just as it's important to understand the formats of your input data, it's also important to understand how the data will be stored and, later, queried. Different types of databases are optimized for different use cases, and it's critical to make the right technology selections in order for you to be able to get all the right answers from your data sets. Our team is experienced in a variety of database engines and technologies, and can help you make the right choices for your specific needs.

Data Transformation and Migration

Once you've decided on a strategy for collecting, storing, and querying your data, it often becomes necessary to transform and migrate existing data to meet the needs laid out by this strategy. Our team can build custom data transformation tools to make this process much easier. Using our tools, you will be able to transform billions of rows of complex data in a very short amount of time. We can help you import and test the newly transformed data into your database and validate it using raw queries or by visualizing it in the BI tools you are accustomed to using.



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