Data Fuels Digital Transformation,
it as 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 Boolean data, 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 ?


We organize and structure large volumes of data, making it easier to use and facilitate better business decisions.


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.


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

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 will work collaboratively with your subject matter experts to choose the right services and accelerators data transformation geared towards your particular use cases while ensuring quality and governance.
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:


Extract knowledge and insights from noisy, structured, semi-structured, and unstructured data, and apply actionable insights from data across a broad range of application domains.



By combining our strong machine learning skills with our expertise in entity extraction, sentiment analysis, and topic modeling, we are able to develop NLP applications that improve process efficiency, customer experience, and retention.



Leverage signal processing and deep learning to capture deeper insights into your image, audio, or video data​. Face detection/authentication, emotion analysis, text extraction, image captioning…these leading use cases that fall right within our expertise


Streamline and accelerate the ML model development and deployment process by using both real-time and batch data processing. AI/ML use cases and various cloud-based machine learning techniques such as AutoML, Hyperparameter Optimization, and Bot Services.

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

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

– CTO & Chief Data Officer

Within a year of our launch, we added more than 20 data sources for our micro lending platforms. These included complex data from core banking systems, mobile and geo data from our partners and a variety of confidential data from different sources. Data engineering is a critical component to process data from all these sources for our data analytics to run and provide scoring for our customers. Boolean’s team did amazing job in putting together a solution that was scalable and robust. Thank you team !!

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Boolean data provides the best cloudplatforms and products to solve real-world business analytics and data problems. We are experts in Business & Digital METAMORPHOSIS We help businesses create new value from data and get faster value on cloud investments.


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Suite #4204, Alpharetta,
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Boolean Data Pvt Ltd
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Hyderabad – 81.

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