The Magic of Big Data

Big Data solutions contain high economic, social, scientific value. We’ve already published a series of articles on how big numbers will transform your business, what niches can benefit from applying Big Data and Analytics as well as what tools and techniques to use to provide your product with a critical competitive advantage in the world market.

In this article, openGeeksLab has described the magic of Big Data, tricks you can perform by using it, and the benefits SMEs get from each of them.

1. Big Data Solutions and Data Mining

Data mining refers to the process of identifying hidden relationships or patterns within large databases and generating new information from them. It is a powerful tool for use in broad areas — statistics, machine learning, artificial intelligence (AI), protection of data security, credit ratings, targeted marketing, fraud detection, etc. Data mining also stands for knowledge discovery of data.

Benefits for SMEs:

  • making better business decisions
  • ensuring lower costs
  • increasing revenues

2. Crowdsourcing Apps

Crowdsourcing is useful in engaging users in representative data collection, creation, editing, and sharing by uploading it on digital platforms in real time. For instance, crowdsourcing is of great help in vast areas as healthcare, government affairs, socio-cultural issues, education, banking, investments, traffic conditions reporting, etc.

Benefits of crowdsourcing:

  • getting fresh insights or solutions
  • reinventing business models
  • tasks optimization, efficiency increase
  • reducing costs
  • driving deeper customer engagement, providing opportunities for collaboration

3. Data Fusion and Data Integration

Data fusion solutions and fusion integration mean a set of techniques that allows gathering, integrating, analyzing heterogeneous datasets from various sources to get insights into how to build more efficient, accurate correlations and models.

For instance, information gathered from social networks and analyzed by natural language processing can be integrated with real-time sales stats and analytics to track customer sentiment as well as identify consumer purchasing behavior.

4. Machine Learning Techniques

Advanced machine learning is the best combo for working with big data analytics as there are large datasets AI can train with, learn from, and find relationships between variables, returning all relevant clues, and providing accurate forecasts. Without an in-depth database, machine learning doesn’t have enough examples to process and, therefore, the results may be inaccurate. One more thing is that machine learning models use algorithms which allow self-updating when receiving new input datasets.

5. Artificial Neural Networks

Artificial neural network algorithm, as a machine learning technique, is trained with available input datasets to process information for solving specific tasks — regression and classification. After using existing AI models and in training, a network can be used to detect patterns in complex databases, predict, forecast, categorize values of dependent variables.

6. Pattern Recognition Technologies

AI pattern recognition is about recognizing and classifying objects via machine learning algorithms — biometric recognition (face detection, fingerprint or iris analysis), speech recognition, medical diagnosis, document image analysis or classification, multimedia data recognition, retrieval, etc.

Benefits for SMEs:

  • solving classification problems by accurate recognizing shapes and objects
  • solving fake biometric detection problem
  • excluding redundant, irrelevant features
  • uncovering unknown casual relationships
  • analyzing environmental scenario

7. Natural Language Processing Techniques

Natural language processing (NLP), as an AI technique, allows understanding and recognizing human speech as well as interpreting the information stored in text files and converting it into structured datasets. For instance, you can monitor social networks or customer reviews to define your business performance, relevant information for your product as well as to highlight areas for improvement. With natural language processing algorithms, search engines provide users with translating speech into other languages, voice, autocomplete search as well as autocorrect feature.

Benefits for SMEs:

  • improving user experience
  • applying chatbots
  • ensuring documentation accuracy, improving its efficiency
  • applying advanced analytics to text files
  • facilitating sentiment analysis performance
  • content categorizing
  • machine translation
  • transforming audio into text, and vice versa

8. Predictive Analytics

Predictive analytics allows you to make accurate predictions about various issues to improve your business facilities. For instance, Amazon’s shopping lists or recommendations use this method. Predictive analytics is a must in fraud detection, healthcare, economics, customer relationship modeling, risk management, tracking consumer behavior.

Benefits for SMEs:

  • delivering a personalized experience consumers
  • continually data processing
  • ensuring security and legal compliance
  • reducing risks and costs
  • getting a competitive advantage in the market
  • improving performance and operational efficiency

9. Simulation Modeling Software

Simulation modeling, which is also known as the Sandbox Concept, is an environment which allows observing and converting complex system behavior findings into clear insights using data analytics.

Benefits for SMEs:

  • building models (financial or operational) and running experiments in a risk-free environment
  • optimizing workflow, saving time, reducing costs
  • enabling a thorough visualization
  • getting insights into dynamics
  • improving greatly forecast accuracy

10. Spatial Analysis Techniques

Spatial data analysis is a type of analysis that allows you to extract or create information about geographic features to perform modeling geo-referenced datasets. Spatial database impacts everyday lives as it helps to interpret, estimate as well as predict events. The analysis has made possible spatial events (crimes, accidents, disease outbreak) analyzing, GPS trajectories tracking, climate model simulations, and other stuff.

11. Statistical Analysis Methods

Statistical analysis for business is a must when working with large static datasets, quantitative and qualitative, with applying the laws of probability to understand whether a particular data set is random or not.

Benefits for SMEs:

  • making data-based decisions
  • predicting future trends in economics
  • simulating business models to improve the planning stage
  • identifying the best business decisions
  • optimizing the workflow

12. Analytical Data Visualization

All is simple — analytical data visualization is about converting datasets into visual form to get better insights. You can showcase big numbers via static or interactive charts, graphs, reports, lists, or maps.

Big Data visualization is prevalent in fintech, healthcare, banking, distribution and retailing, etc.

Importance of data visualization:

  • identifying bottlenecks
  • carrying out a customer sentiment analysis
  • sales forecasting
  • ensuring faster response to market trends
  • a better understanding of the workflow

Big Data in Action to Grow Your Opportunities

Now you know how to use the power of Big Data solutions to the fullest. But which solutions to choose so that they work best for your business depends on your objectives and the opportunities you need to grow.

We at openGeeksLab know how to convert raw data into unique business solutions to provide your product with a competitive advantage that is not available to an average SME.

If you have any further questions, please don’t hesitate to contact us at

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This article was originally published on the openGeeksLab blog.