Advanced analytics solutions

  • Increase your understanding of customer behavior and optimize your retention strategy with real-time analytics of structured and unstructured customer data

  • Detect and prevent cybersecurity risks and get recommendations on how to strengthen your digital infrastructure against potential threats with custom advanced analytics software

  • Reveal new business opportunities and increase competitiveness with tailored predictive analytics solutions

  • Gain insights into business processes as a whole and improve strategic business planning with interactive reports and deep-dive big data analytics

Value we have delivered to our clients

  • Up to 30%

    improvement in business performance with predictive analytics

  • 15+

    successful advanced analytics projects

  • 97%

    average customer satisfaction rating across industries

  • Up to 10%

    increase in market share

Advanced data analytics solutions and services Yalantis provides

Scale your data analytics capabilities by leveraging cutting-edge technologies and partnering with well-rounded experts in big data analytics, IoT analytics, and AI/ML.

  • AI and ML analytics

    • Data analysis using advanced technologies such as AI, ML, and deep learning

    • Modernization of existing advanced analytics practices to fit changing business needs

  • Big data analytics

    • Implementation of a data analytics architecture layer

    • Big data analytics tool selection

    • Integration of dashboards and data visualization tools

    • AI/ML implementation for predictive real-time analytics

    • Data classification and labeling for simplified search

  • IoT analytics

    • IoT data management

    • Data collection and aggregation

    • Data visualization and dashboards

    • Real-time monitoring and alerts

    • Predictive maintenance

Increase business process transparency and improve performance with advanced analytics software

Uncover meaningful business insights and patterns by gathering and analyzing large volumes of structured and unstructured data.

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FAQ

What types of advanced analytics software and services do you offer?

Our team of data experts is experienced in all types of advanced analytics services such as big data analytics, IoT analytics, and predictive and prescriptive analytics.

  • Predictive and prescriptive analytics require integration of an ML model for making accurate business forecasts and coming up with recommendations that can help you prepare your business for unexpected changes.
  • IoT analytics can derive insights from IoT data so that you can use these insights to improve or expand your IoT device fleet.
  • Big data analytics can be suitable if you need to gain the most well-rounded understanding of your business, as this type of analytics undermines work with all types of data coming from all external and internal data sources.

How do you suggest suitable advanced analytics tools?

Our data engineering team analyzes your current IT infrastructure and existing data analytics practices to define which tools you can easily use without disrupting your established workflow. The technologies and software you currently use at your company are decisive in picking fitting analytics tools. If you frequently extract data from legacy systems for advanced analysis, we first need to check which analytics solutions can integrate with these data sources. Your scalability expectations are also important when choosing advanced analytics software, as we need to ensure your software can handle future data growth.

What’s your approach to integrating advanced data analytics solutions?

Our approach involves designing a detailed implementation plan and roadmap to make advanced analytics integration iterative and smooth. This plan includes:

  • exploring all of your data sources and their accessibility
  • defining data quality and integrity
  • ensuring regulated data processing
  • implementing data cleaning techniques

All of these preparation steps are important for seamless integration and further use of advanced analytics tools. Yalantis data experts prioritize collaboration and will keep you informed at every step of the integration process.

 

Our team of experienced data engineers, data scientists, and analysts also prepare detailed documentation you can pass to your in-house team to ensure proper advanced analytics system maintenance and support.

How do you address industry-specific concerns regarding advanced analytics solutions?

As an advanced analytics company, we understand that analytics needs and requirements can vary significantly across industries. Each business in a particular domain is subject to a particular set of laws and regulations, uses specific data sources, faces specific market conditions, and has particular issues to solve, and we tailor our advanced analytics services accordingly. We have a pool of diverse domain specialists who can be consultants on the project or work with clients on a regular basis. In addition, our research and development departments constantly investigate emerging technologies and shifting customer needs in diverse industries such as IoT, FinTech, healthcare, and manufacturing to stay in the loop of the latest IT advancements and suggest relevant solutions to our clients.

Beyond descriptive analytics with Yalantis: Checklist for successful advanced analytics integration

Yalantis is your trusted advisor and partner in defining whether advanced analytics is the right option for your current and future business needs. With our expertise and guidance, we empower you to navigate the complexities of data-driven decision-making and unlock the full potential of advanced data analytics solutions by predicting customer behavior, optimizing supply chain operations, or identifying emerging market trends.

Before delving into advanced analytics, it’s essential to assess your organization’s readiness and whether advanced analytics initiatives align with your current and strategic business objectives. Let’s take a closer look at five key questions you can ask yourself to determine if advanced analytics is the right fit for your business:

1. What is our company’s current data infrastructure?

You should have a proper understanding of your existing data capacity and data sources as well as the strengths and weaknesses of your existing data architecture. These insights can help you make informed decisions about how to best leverage your data assets for advanced analytics initiatives. Assessing your current infrastructure is crucial to identify any gaps or areas for improvement that may hinder the successful implementation of advanced analytics solutions.

If you find it difficult to assess your current infrastructure with your in-house team, Yalantis data engineers can conduct a thorough data infrastructure assessment for you. Our team of experienced data specialists will analyze your data architecture, including data storage systems, data repositories, data processing pipelines, and integrations. As a result, they will identify bottlenecks, security vulnerabilities, and performance issues that may impact your ability to derive actionable insights from your data.

2. What are our company’s current data analytics priorities?

Answering this question can compel you to reprioritize your data analytics needs, as you may discover that currently you are analyzing key performance indicators (KPIs) that no longer provide relevant insights. In that case, you need to reassess your analytical priorities, redefine your KPIs, and realign them with your overarching business goals. By recognizing potential misalignment between the insights you’re generating and the actual needs of your organization, you can pivot toward addressing high-impact challenges and opportunities with advanced data analytics solutions. This proactive approach ensures that your data analytics efforts remain agile and responsive to evolving business and industry dynamics, ultimately driving meaningful value and a competitive advantage.

Furthermore, answering this question can help you realize what technologies you could use on top of data analytics to drive greater business benefits and value. Understanding the technological side of data analytics opens a window of opportunity for acquiring more tools and platforms that can enhance the depth and breadth of your analytical capabilities. Whether you’re adopting machine learning algorithms, implementing real-time data processing frameworks, or using powerful visualization tools, knowing which technologies align with your business objectives empowers you to make balanced investments in your analytics infrastructure.

3. How can our company improve current analytics practices?

Though you may find it challenging to thoroughly answer this question without consulting an advanced analytics company, considering this question can still help you see the potential for improvement in your current data analytics practices, allowing you to critically evaluate the effectiveness of your existing data analytics methodologies.

For instance, you may realize that traditional business intelligence and historical business analysis with dashboard building aren’t helping you in composing a long-term business improvement strategy, and that’s when advanced analytics can come in handy. While traditional approaches may provide valuable insights into past performance, they often fall short in predicting future trends and enabling proactive decision-making. Advanced analytics techniques, such as predictive modeling and prescriptive analytics with machine learning, empower you to uncover hidden patterns, forecast market shifts, and anticipate emerging business opportunities.

4. What business value do we expect from improved data analytics?

Integrating advanced business analytics solutions is only worthwhile if they cover your needs. The major value of analytics is to drive decision-making by providing you with actionable insights. However, advanced analytics takes this a step further, offering a multifaceted approach that goes beyond mere analysis of historical data. Instead of relying solely on past trends and patterns to inform decisions, advanced analytics empowers organizations to anticipate future outcomes and proactively shape their strategies.

The true power of advanced analytics lies in its ability to enable proactive decision-making rather than helping with taking reactive measures, which are often the result of historical data analysis. By leveraging sophisticated techniques such as predictive modeling and the application of machine learning algorithms, advanced analytics transforms raw data into foresight. Advanced analytics highlights potential scenarios and outcomes, allowing businesses to anticipate trends, identify opportunities, and mitigate risks before they materialize.

Advanced analytics also guides organizations toward informed and forward-thinking decision-making. By harnessing the power of predictive analytics and machine learning, organizations can unlock new opportunities for innovation, efficiency, and achieving a competitive advantage in the ever-evolving business world.

5. What are potential use cases for advanced analytics at our organization?

Identifying potential use cases for advanced analytics in your organization is crucial for maximizing the impact of data-driven decision-making. Applying advanced analytics solutions across all departments can be overwhelming and inefficient. Instead, taking an iterative approach allows you to prioritize and focus on areas where advanced analytics can deliver the most significant value:

  • Optimizing marketing campaigns
  • Improving supply chain management
  • Enhancing customer segmentation
  • Predicting equipment failures in manufacturing processes
  • And so on

Advanced analytics offers a wide range of applications across various business functions.

For example, if your organization is struggling with high customer churn rates, you can apply advanced analytics to analyze customer behavior patterns, identify factors contributing to churn, and develop predictive models to proactively address customer attrition.