Data fuels digital transformation, it is at the heart of everything an
enterprise aspires to do.
Data Transformation is one of the exciting avenues for enterprises to migrate and streamline data. Use our services to drive digital disruptions by harnessing data at scale.
We help customers to unlock the true
potential of their data.
At Booleandata, by placing user needs at the epicenter of our data transformation efforts, we are able to deliver an impactful, delightful, efficient, and result-oriented experience.
Businesses need to transform high volumes of data for several reasons, such as migrating data, consolidating records, etc. To be able to manipulate data in the most effective way, a data transformation tool with a broad array of transformation options is necessary.
Why Boolean Data ?
Usability
We organize and structure large volumes of data, making it easier to use and facilitate better business decisions.
Quality
We ensure proper formatting, validating, and managing of data. “Bad data” issues like metadata inconsistencies, indexing errors, incompatible formats, duplicate records, and missing values are reduced significantly.
Efficiency
Using our cutting-edge transformation tool, you can improve data efficiency by exchanging data between APIs and cloud apps, all from one simple platform.
Timely and
affordable
By providing complete visibility, we are able to execute on time. Also, the best of our data transformation services comes with multiple functionalities, which are both unique and affordable.
How will our services benefit you?
We guide you through the entire process, working closely with your company, its challenges, strategy, and any questions you may have. Let’s look at some of the fields we can help your business with:
Data Integration
We offer a complete data integration
solution that combines data from multiple separate business systems into a single unified view, often called a single view of the truth.
Data Migration
Data Wrangling
Data Warehouse
A Boolean approach to data transformation
Extraction and parsing
In the modern ELT process, data ingestion begins with extracting information from a data source, followed by copying the data to its destination. Initial transformations are focused on shaping the format and structure of data to ensure its compatibility with system.
Translation and mapping
Some of the most basic data
transformations involve the mapping and translation of data. Translation converts data from formats used in one system to formats appropriate for a different system.
Filtering, aggregation, and summarization
Data transformation is often concerned with whittling data down and making it more manageable. Data may be consolidated by filtering out unnecessary fields, columns, and records. Data might also be aggregated or summarized.
Enrichment and
imputation
Data from different sources can be merged to create denormalized, enriched information. Long fields may be split into multiple columns, and missing values can be imputed or corrupted data replaced as a result of these transformations.
Indexing and ordering
Data can be transformed so that it’s ordered logically or to suit a data storage scheme. In relational database management systems, for example, creating indexes can improve performance or improve the management of relationships between different tables.
Modeling, typecasting, formatting, and renaming
Finally, a set of transformations can be applied to data without changing its content. This includes casting and converting data types for compatibility, format localization, and renaming schemas, tables, and columns for clarity.
Client Testimonials
For more information on how to execute transformation like a master, please contact us.
Interested in building data solutions?