Advanced-Data Analytics

Advanced Data Analytics is the autonomous and semi-autonomous examination of data, leveraging machine learning (ML) and artificial intelligence (AI) technologies beyond modern business intelligence (BI) to understand what happened, why it happened, what will happen, and what steps to take. 

There are four tiers to Advanced Data Analytics:

  • Descriptive Analytics: this is the baseline of analytics where you
    discover what happened in your business through descriptive data reports.
  • Diagnostic Analytics: through analyzing the descriptive data, you can
    uncover why certain events happened through applying diagnostic analytics, which includes techniques like
    drill-down, data discovery, data mining, and correlations.
  • Predictive analytics: here is where you can leverage both of the previous
    tiers and use deep learning and machine learning to analyze massive datasets, notice patterns within them,
    predict results, and consider probabilities.
  • It depends on past and real-time data from multiple sources and formats. It
    fills in missing data with predictions based on observations from the rest of the datasets. It uses
    regression analysis, forecasting, multivariate statistics, pattern matching, predictive modeling, and
  • Predictive analytics helps your business executives set SMART goals, have a
    proactive approach, and mitigate risks.
  • Prescriptive analytics: this is the last, most difficult, and most
    rewarding tier; the success of prescriptive analysis depends on the quality of data needed, the appropriate
    data architecture to facilitate it, and the expertise required to implement this architecture.

This process will help executives, marketers, and financial advisors make decisions backed with data and feel assured that the results of these decisions are favorable.

Advanced Data Analytics
  • Data Mining

    Data mining technologies help you predict future events, recognize opportunities and mitigate risks.
    Through this technology, you can:

    • Facilitate data preparation: by using dynamic charts and graphs, you can understand and interact with the direct and in-direct main data relationships.
    • Swiftly build enhanced models: by implementing solid techniques and a drag-and-drop interface, you can build accurate and reliable models.
    • Deploy your models: You can score new data effortlessly by using automated and interactive processes that perform in batch and real-time environments.
  • Statistical Analysis

    Statistical Analysis will help you get accurate answers whether you are analyzing customer data, sales numbers, monitoring supply chain operations, or trying to detect fraud.
    Using this technology will help you:

    • Analyze the past, describe the present, and predict the future: using advanced quality-tested, continuously updated algorithms to match the modern statistical methodologies.
    • One technology covers all: analysis of variance, regression, categorical data analysis, multivariate analysis, survival analysis, psychometric analysis, cluster analysis, nonparametric analysis, mixed-models analysis, survey data analysis, and much more.
    • Customizable to your needs: produce task-specific graphics. Create analytical-style graphs, maps, and charts with various output styles to deliver resourceful and accurate analytic results.
  • Forecasting

    Leverage automation processes to produce high-quality predictive analytics and streamline your forecasting process to shift your focus on the decision-making process.
    Using this technology will help you:

    • Limit the effects of personal bias: using integrated automated processes will limit the occurrence of human intervention, and thus the data will not be tampered with or exposed to political and personal biases.
    • Access powerful forecasting techniques without coding: using Graphical User Interface (GUI), you'll be able to harness the power of forecasting without writing code and provide tech-savvy users with access to batch environments and their capabilities.
    • Leverage our model repository to plan for the future effectively: A virtually unlimited model repository provides models for a wide range of behaviors, enabling you to test scenarios related to your field and implement future strategies based on the outcome. You'll also be able to consider both planned and unplanned events. And mine, segment, and visualize data interactively.
  • Text Analytics

    90% of your data is unstructured!
    Instead of leaving it unattended, why not make use of it? Through our text analytics technology, you can:

    • Assess text leveraging AI: discover insights within extensive text data using advanced linguistic rules and analytical modeling tools.
    • Automate manual processes: leverage Machine learning and natural language processing techniques to automate manual processes and use the environment's capabilities to swiftly assess extensive text data collections.
    • Customize rules based on your business needs: improve discovery by reviewing categories identified by machine learning, and write and edit rules based on definitions and classifications that are important to your organization, as well as, validate any changes and test them against validation samples.
  • Optimization and Simulation

    Using this technology, you can discover scenarios that will produce your organization's desired results. We can help you:

    • Model and communicate the best solutions to solve your complex issues.
    • Get better results: Use a wide range of operations research methods – including optimization, simulation, and project scheduling techniques – to evaluate, modify, and incorporate additional information.
    • Integrate your analytics: implement optimization, simulation, and scheduling techniques in data management.
  • Behavioral Intelligence and Analytics

    Scale large volumes of data by leveraging our terrarium database engine and scalable real-time data analysis to have unlimited access to control of large amounts of data in real-time, with virtually unlimited retention.
    By using behavioral intelligence analytics, you’ll be able to:

    • Use a robust proprietary database to help you get real-time data processing results.
    • Set your own advanced KPIs or use the most imported ones.
    • Reduce your churn rate by setting up churn analytics to understand why customers leave and how you can increase your retention rate.
    • Leverage AI-based segmentation to help you understand your customers and drive conclusions that you can use in the future.
    • Create customized reports fast, thanks to the drag and drop campaign report generator.
    • Import historical data directly to your heterogenic real-time database easily.
    • Set up a two-way API connection to connect any data to the platform or send it directly to your systems.
    • Utilize advanced performance management using fully configurable and responsive reporting options to achieve your imperative business goals.
  • Analytic Fields

    • Funnel Analytics: Understand how your customer flows in the funnel and enhance stages and touch-points to increase conversions.
    • Geoanalytics: Market geo-based campaigns to your segments and gather geo-related insights on your customers.
    • Campaign analytics: Analyze your campaign and locate areas of improvement to launch more successful campaigns in the future.