Data inference

Data analysis professional service

Based on each customer's business objectives, we employ the state-of-the-art data theory, toolbox, and methodology to help our customers gain the best of benefits from a variety of data resources.

Techniques: descriptive analysis, regression analysis, cluster analysis, structural equation modelling, time series modelling, hierarchical equation modelling, panel data analysis, machine learning, data mining, etc.

Focused field

  • User analysis
  • Precision marketing
  • Forecasting and Simulation
  • Recommender system


Our workflow process gets customers fully involved. Customers will receive frequent project updates and be invited to participate in interim discussions.

Data solution

Data analysis professional service

In the era of data technology (DT), few companies and organizations could avoid the problem of dealing with a huge amount of data. With the increase of data in terms of volume, variety, velocity and variability, DT often involves the combination of traditional database, NoSQL data store, Hadoop Distributed File System (HDFS), data streaming, data modelling, and machine learning.

However, not all of the companies and organizations have the competency to appropriately utilize all these technologies, control the veracity of the data, and discover the value of data. If you are struggling with similar situations and doubt the hype of Hadoop (Luckily you are right, Hadoop is definitely not the only resort for your data problems. Actually, in most cases you may not need Hadoop at all.), DatatTellIt may help you out no matter you just start setting up a small database or have already accumulated years’ of data. Again, as an advocator of the principle of parsimony, we will provide you succinct but effective solutions with affordable price.

Data infrastructure planning

  • Investigate into existing DB infrastructure and figure out bottlenecks
  • Identify current problems and potential risks
  • Architecture design of an integrated data system
  • Advice on the selection of physical platform, such as on-premise, private cloud, virtual private cloud or public cloud
  • Advice on the selection of data containers, such as SQL/New SQL, NoSQL, column stores, and data grids.
  • Advice on optimization in terms of architecture and infrastructure, such as main memory database, replicas, and parallelism.
  • How to take the advantage of open source resources
  • Build up your own data administration and development team

Database design

  • Review existing database design and pertinent applications
  • Locate problems and reveal the causes
  • Estimate the on-going changes in a reasonable period
  • Design new logic schema and/or retrofit existing DB schema
  • Propose database physical design
  • Interface design
  • Advice on optimization of data query
  • Evaluate the performance of new design

Data security proposal

  • Loopholes detection for existing data system
  • Potential data security risks discovery
  • Policy compliance
  • Data security improvement proposal
  • Data system contingency plan

Big data strategy

  • Big Data strategy development and assessment
  • Data resource planning
  • Data integration and ETL solution
  • Real-time streaming data solution
  • Machine learning on Big Data
  • Knowledge transfer

Value chain co-op


We welcome our business partners to join all the activities in the value chain. Our business solutions are customized and flexible so that each of our business partners can bring in their existing advantageous activities. We will provide the other missing activities to complete and extend the value chain.


By discovering critical information and knowledge from Big Data, values can be added through improved marketing and sales, extended services, and platform aggregation effects. It is a win-win situation for both sides.

Possible partners

  • Retail
  • Advertising
  • Health Care
  • Community Services
  • And more...