We work on data analytics at all stages and levels, from unstructured data coming from various resources to well-structured data. We use powerful analytical software such as SQL, Python, SAS, and Microsoft Enterprise BI & platform suites to design and develop algorithmic computer programs. The analytical programs can process data to create data tables for databases and datasets for analysis. 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 deeper data analyses, such as predictive analysis, Bayesian analysis, decision support analysis, reporting, and AI applications.
* Data Processing and Cleaning
* Data Integration
* Data Transformation
* Measurement Creation
* Summary & Trend Analysis
* Exploratory Analysis
* Clustering Analysis
* Sentiment Analysis
* Data Visualization
* Algorithm Development
Data can come from various resources in various forms, such as internal operation systems, external files, and log files in forms of cvs, xls, txt, xml, etc. Raw data needs to be cleaned and processed to trim out noise, and then recoded and restructured to make data useful and meaningful.
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 recoding, transforming, and restructuring, which are important to facilitate sensible data analyses .
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 business insights.
Nowadays, business operations and strategies need deeper knowledge about operations, products, and customers 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.
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.
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.
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