Big Data Analytics


We work on data analytics at all stages and levels, from unstructured data coming from various resources to well-structured data. We use powerful data analysis software such as SQL, Python, SAS, and Microsoft Enterprise platform suites to manage data and design and develop algorithmic computer programs. The advanced data ETL and management tools enable us to transfer various types of data into a data management system, and then we develop computer programs to analyze data and create data tables for databases and datasets for analyses. We conduct various data analyses to reveal facts, patterns, trends, and insights. The results can then be presented in tables, charts, and maps. Furthermore, we offer deep data analyses, such as predictive analysis, machine learning, decision support analysis, reporting, and BI & AI applications.

We use the latest data management and analytics platforms that enable us to seamlessly process various forms of data, including datasets from databases and in forms of excel, csv, txt, html, PDF, and data from websites. After gone through our data integration, analytics, and application development processes, the data will turn into valuable business insights, strategies, and business tools. The output data formats can be web applications, mobile applications, online reports, and files in excel,  txt, csv, and FDP formats. 

Typical Projects:

*  Data Processing and Cleaning

*  Data Extraction and Loading 

*  Data Integration

*  Data Transformation

*  Measurement Creation

*  Summary & Trend Analysis

*  Exploratory Analysis

*  Monitoring & Alerting

*  Outlier Detection

*  Data Visualization 

*  Algorithm Development 

Data Processing & Cleaning


Data can come from various resources in various forms, such as from various sources like internal devices, data vendors, websites, log files in forms of database dataset, cvs,  xls,  txt, xml, PDF, et. Raw data needs to be cleaned to trim out noise, extracted for useful information, and then transformed and structured to make data useful and meaningful. 

Data Integration


Data integration is a process to get data consistently and accurately representing and measuring objects or activities, and to structure data in data tables residing in databases. Data integration involves data transferring, recoding, transforming, and restructuring, which are important to facilitate data analyses. 

Measurement Creation


In business analysis, creating the right measurements are crucial because they define what analysis is for and how deep analysis will go. For different industries and  projects, measurements are different. For deeper analysis, more complex and detailed measurements are needed in order to uncover tangible business insights and develop special function applications. 

Deep Data Analytics


Nowadays, business operations and strategies need deeper knowledge about operations, products, and markets in order to provide the right products and services. Deep data analysis can help reveal insights of facts, discover cause and effect relationships, recognize hidden patterns, and predict possible events. 

Algorithm Development


All big data analyses are performed by computer programs. Analytical algorithms are a series of computer instructions which instruct computers step-by-step to do the jobs. We develop algorithms for data processing, integration, reporting, deep data analysis, predictive modeling,  and automatic prediction and detection and recommendation in SQL, Python, and SAS.

Data Visualization


One picture is worth a thousand words. Data visualization is to present data in tables, charts, and maps. We analyze data and visualize results in  interactive tables,  charts, and maps. Users can drill down and drill through visuals to obtain more detailed information on desktop  and mobile devices.