As the volume and availability of data skyrocket, it becomes increasingly challenging to transform data into improved business opportunities. That said, it is essential to have the right information at the right time to get a single view of business operations and quicken the pace of data analysis and visualization. This will help organizations to identify factors that affect business performance and drive fundamental change in business operations.

Our Data Science and predictive analytics service enables organizations to develop customized statistical and machine learning models to leverage advanced customer, operational and stream analytics in real time. With our solutions, you can provide the right information to everyone in your enterprise - including in-depth analysis and reporting capabilities that are required to understand business, make the right decisions, gain the competitive edge and increase profitability.

Data Science Offers

Our Key Differentiators

Applexus’ Data Science and Predictive Analytics solution offers multiple advantages:

  • Help enterprises quickly create and deploy impactful Data Analytics solution
  • Improving the customer experience - Know the voice of the customer and identify social networks to incorporate sentiment, preferences, and opinion into ideation and product research. This leads to greater customer satisfaction and a much-enhanced customer experience.
  • Lower risk – By using advanced technologies, we can help you reap the benefit of shorter time-to-insights, enabling a proactive approach to risk management.
  • A dedicated team with big data analytics expertise
Competencies

Our Competencies

Our data science and predictive analytics solutions help organizations to establish a data-driven and analytics-enabled culture that systematically use the power of big data to make significant strategic decisions and drive their businesses forward. We use cutting-edge algorithms to help you uncover insights that can benefit your business.

Machine Learning

Big data analytics

Traditional BI systems rely on hypothesis-driven reporting by analyzing past data. With data growing in both complexity and volume, traditional data processing software become incapable of handling data. We harness cutting-edge technology to help organizations analyze massive volume of data from different sources to anticipate uncertainties and proactively react in a dynamic business environment.

Deep Learning

Decision modeling and management

Perceiving big data as you did with your old data will escalate the cost. As a decision modeling and management partner, we help you identify the potential business value of big data, deploy improved decisions to achieve business objectives, discover automation opportunities and determine the best analytics solutions to suit your business needs.

Natural Language Processing

Statistical analysis and visualization

To create an interactive and complex visualization for easier decision-making processes, data visualization tools alone may not suffice. This justifies the need for advanced predictive analytics software with a robust back-end to handle huge volumes of messy data end-to-end. We use state-of-the-art modeling, analysis and visualization techniques to improve understanding of complex problems through data analysis.

Machine Learning

Predictive modelling

Big data acquires value from the insights it generates when analyzed – in the form of critical decision making, optimized processed and deepened engagement with customers. However, relying on big data to analyze events in the past alone will not help businesses. Our team of data scientists analyzes real-time and batched data and combines them with advanced statistical and machine learning algorithms to model effective analytics solution from the ground up.

Our approach to development

Our approach

Even as data is created more than ever before, most companies fail when it comes to gleaning marketing insights. Either there is a lack of data science specialists or the team is too small to handle the requirements of a fast-growing company. Our team of data experts can help you make proactive use of data and equate it into greater revenues. We can help you identify the root cause of the challenges you face today
and smoothen out business processes efficiently.

We follow a simple three-step process to develop data analytics solutions.

  • Initial Assessment

    Understanding your business priorities and project goals is often the first step in any implementation projects. After this phase, we meet up with your business and data leaders to get a firm grasp of your business metrics, which may be examples of raw data. This process will help us make a formal project assessment and create a project implementation plan.

  • Proof of Concept

    We will work with you to understand the challenges you face in your business, your business objectives, understand your data, recognize project goals and identify results to be achieved. After this, we assess how best a data model will encapsulate the concepts of an organization and build proof-of-concept data analytics solutions that can create high-impact business outcomes.

  • Model Development

    We prepare your historical data sets, sample it and adopt an iterative approach to generate the best algorithm or model. Such successful prototypes are developed into data models that lend itself to the defined business objectives. The models will utilize historic data to analyse new datasets and predict future trends with improved precision.

  • Full Stack Application Development

    We have experience in creating enterprise-wide analytics solutions based on cutting-edge big data technologies that deliver tangible business benefits from data. Every layer of the application from the backend to frontend is developed with extra care to allow intuitiveness and easy access to reports and visualization.

  • Model Management

    Knowing that most models are rendered ineffective over a period, we provide support to keep the model up-to-date by refreshing it with latest data. We can maintain, monitor, and fine tune your models and applications for greater precision and efficiency and help your business grow and evolve.

  • Model Testing

    All models and applications are continuously subjected to rigorous test to detect and fix security anomalies, scalability bottlenecks, and performance breakdowns.

Technologies

  • python
  • rlogo
  • apache-spark
  • strom
  • kafka
  • flume
  • Tensor Flow
  • PyTorch
  • kudu
  • redis
  • cassandra
  • apache-hbase
  • Elasticsearch
  • Docker
  • Cloudera Impala
  • hadoop
  • hive
  • apache-pig
  • tableau
  • tech_DB
  • graphx
  • Plotly
  • Kibana
  • Power BI
  • amazon-web-services
  • azure
  • SAP-leonardo
  • ibm-watson
  • WSO2
  • MuleSoft