Enhance
Refine &
Optimize

Data Enrichment

Our Data Enrichment Process

01

Identify The Problem

Knowing why you need to enrich existing data is a crucial step of the entire process. This will help determine which kind of data will be more valuable after collection.

02

Define Data Collection Methods

Identify appropriate technologies and processes for data collection and enrichment. At this point, we pay attention to data fragmentation as well.

03

Check Data Quality

Even the most sophisticated algorithms cannot work if the quality of data is not up-to-mark. We conduct frequent quality checks to ensure that the database is error-free.

04

Maintain Data Consistency

Since we aggregate data from various sources, we format it to eliminate any possible inconsistencies.

05

Data Cleansing

Once data is collected, we carry out data cleansing wherein we identify and remedy incomplete, inaccurate or irrelevant information. This helps us provide you with the highest quality data.

06

Decomposing & Discretizing

For easier understanding, we decompose data into multiple simpler sections. Alternatively, we discretize it, converting specific numerical attributes into categorical kinds.

07

Merge Transactional and Attribute Data

Transactional data captures specific moments whereas attribute data is something that is permanent. We merge the two to facilitate better predictions.

08

Data Normalization

In this step we improve the quality of the database by reducing the dimensions. This way we avoid a scenario where one attribute may outweigh another.

COMPANY FEATURES

Creating sustainable impact for firm with long term vision since it’s establishment

Company Mission

Company objective

Data Enrichment
Data Enrichment
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