Scale on data you trust,
not messy spreadsheets.
Your supplier data is inconsistent. Pricing lags. Your team wastes time on manual fixes. DevPals builds automated data pipelines that validate and clean your data in real-time so you scale inventory, pricing decisions, and revenue with confidence.
We use Big Data analysis based on first- and third- party data
More than 40 000 data points on your customers, ranging
from recent purchases to loans, to unleash insights on segments and achieve:
1
Targeted Acquisition
Customized look-alike profiles for top-performing traffic
2
Better Conversion
Profiling-based custom funnels
3
Personalised Retention
Individualized messaging and product experience
4
Sales Automation
When it comes to messaging, sales cannot connect the dots
DevPals stands at a data fork in the road and acknowledges the business need to enhance client interactions and business processes.
We understand how big data profiling and analysis can aid in data quality control during the era of the digital transformation.
We simplify the process of exploring and rebuilding complex big data lakes, leading to a truly digitally connected businesses.
Unveil five exciting anticipated data breakthroughs by clicking here!
What is our process for choosing a database?
When it comes to selecting a database, we take into account both Relational Database Management Systems (RDBMS) and NoSQL databases, in order to gain a comprehensive understanding of each ecosystem. We evaluate different systems based on factors such as data type, storage, structure, and intended use, with the goal of meeting the specific needs of our clients. Additionally, factors such as required consistency, latency conditions, and transaction speed, including real-time querying mechanisms, may also play a role in the decision-making process.
DevPals Big Data Profiling Practices
Basic
Basic techniques
3 techniques
01.
Distinct count and percent
Identifies natural keys — distinct values in each column that aid in the processing of inserts and updates.
02.
Percent of zero / blank values
Identifies data that is missing or unknown. Assists ETL architects in establishing appropriate default values.
03.
Minimum / maximum string length
To improve performance, you can set column widths to be just wide enough for the data.
Advanced
Advanced techniques
3 techniques
01.
Key integrity
Ensures keys are always present using zero/blank/null analysis. Identifies orphan keys — problematic for ETL and future analysis.
02.
Cardinality
Examines one-to-one, one-to-many, and many-to-many relationships between related data sets. Assists BI tools in correctly performing inner or outer joins.
03.
Distributions
Checks that data fields are properly formatted. Data fields used for outbound communications — such as emails and phone numbers — are verified and well-formed.
Gain a competitive edge with DevPals' Data Intelligence and AI tools and say goodbye to costly errors in databases.
No commitment. No sales team. Reviewed by a senior engineer.
DevPals Ltd is a company registered in England and Wales (Company No: 10653250). Fully GDPR and UK Data Protection Act compliant.
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