Outsourced Data Engineering Service

Our clients typically need to quickly complete their machine learning projects. They also need to be flexible and nimble without adding head counts. Our outsourced data preparation service takes care of your ETL tasks (Extract, Transform, Load) and delivers quick and accurate data for their needs. We help with the 80% part that slows down the analytics portion.

This 80% typically involves :
Data preparation tasks like Data Digitization, Data Aggregation/Consolidation, Data Entry, Data labeling.

Our trained and experienced teams off load these tasks and help your team accelerate your data analytics projects. We understand your needs. We can work with Microsoft Access, PDF files, Excel, Statistical files and connect to data on Amazon Athena, Aurora, EMR Hadoop Hive, Redshift, Microsoft Azure, Apache Drill, Aster Database, Cloudera Hadoop, Denodo, EXASOL, Google Cloud, Horton works Hadoop Hive, IBM DB2, IBM PDA (Netezza) and more!

Data Digitization is involved with scanning paper based forms and applying OCR with human editors to ensure that the digitized data is accurate. Most often, data are in different silos. Our teams can consolidate this into one dataset for your teams to work on.

Typical Tasks at this stage includes:

  • Cleansing
    (Correcting inconsistent Data, renaming field names and formatting, outliers and grouping common values)
  • Integration
    (Union and Joins of various input sources)
  • Transformation
    (Aggregation, creating new calculated fields, pivot data, creating links among data sources and reshaping data)
  • Annotation
    Data, Text, Image, Video, Audio labeling service to provide your machine learning project with Labeled Data.
  • Reduction
    (removal of unwanted data)

Data Entry involves human intervention in completing those missing values that would otherwise invalidate the records. Data editing is also needed to normalize the inputs as well.

Finally, data labeling (Annotation) helps you train your AI process. Our teams have labeled hundreds of thousands of images for past projects.

Finally, our project managers have data analytics background that understands your team’s need for data quality. Contact us for a zoom conference to find out more.

When to Outsource?

People usually think that companies outsource some of their functions to save on money. While this has been true in the early days of outsourcing where companies enjoyed the savings from properly implemented plans, they  have also realised some additional benefits from outsourcing. Generally, when either one or more of the following occurs, it is best you consider Outsourcing as a viable option:

  1. Vacant positions are open for a long time.
    Your HR is facing a dwindling pool of qualified people for the open positions. In a tight labor market, outsourcing lets your HR source from a wider pool of potential star performers. You won’t be limited to hiring from your immediate vicinity.
  2. Uncertainty with Market conditions. 
    Management would like to have a more flexible and nimble operation that is not weighed down by a high fixed headcount. Think: Peak and low seasons. It is nice if you can forecast the future growth of your operations, and maintain your staff, but what happens in a downturn? It is easy to hire, and sadly, hardest to fire/layoff people.  By outsourcing your spillover work, you maintain that flexibility and are relieved of having to lay off extra workforce in low seasons.
  3. Quicker time to Market.
    Sometimes your project/s needs that top talent and you can’t wait to train/develop your in-house talents. Outsourcing enables your company to tap on the expertise and specialization of outsourcing companies in what they do best. Your in-house talents can work beside your outsourcing provider and hopefully, your inhouse talents can absorb the best practices and accelerate their own expertise.
  4. Minimizing Operational Risks.
    Sometimes, it just makes sense to ‘not put all your eggs in one basket’. Outsourcing enables your company to spread your manpower over geographic distances. This makes a lot of sense when the next global pandemic or catastrophe hits your main operating region.