WHAT IS IT?
Data Engineering extracts and transforms raw, noisy Big Data from many sources into a clean, rationalized smaller Answer Set suitable for analytic modeling, to provide business decisions.
Our Data Engineering service supports client data scientists, engineers and analysts with a high-quality, economical and rapid data extraction and data storage solution.
Our experts deploy an extensive array of data tools such as Hadoop and Spark, to deliver high-quality data sets ready for further analysis or visualisation:
WHO IS THIS FOR?
Companies fully loaded with concurrent projects and no time for data extraction
Businesses without their own qualified data scientists
Firms whose in-house data scientists are all busy
Companies with budget issues who need an economical data engineering solution
WITH Data Engineering YOU GET:
A dedicated team of Data Scientists
including four PhDs and consultants with more than 100 aggregate years of business and technology experience
Faster turnaround for data analysis and data presentation
for quicker answers to your questions
Extraction and cleaning performed by data scientists
with best of breed tools. This translates into more available time for data scientists to analyse/model the Answer Sets
More time for your data scientists
to analyse, in turn means higher quality business decisions
Reduced cost of data engineering
with data scientists in the cost-effective location
Clean data from raw resources
for better business decisions
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Extract and clean the raw data that your data scientists hate
HOW IT WORKS
Ciklum creates a dedicated team of highly-qualified professional Data Scientists to set up the project in consultation with you
The Data Engineering team performs iterative data transformation, cleansing, repair, aggregation, and representation of data from any kind of source
Relevant data is extracted and stored in appropriate storage solution. Extracted data is available for consumption by tools further along the data pipeline. We define method of collecting, storing, extracting and organising data (Data Architecture)
Clean data set is provided to your own data scientists and business users for use in business analysis