Tag: data visualization

data and analytics

Weekly Round-up: A Storyboard on the Importance of Data and Analytics for Businesses

LONDON: Quantzig, a leading analytics services provider, has announced the release of their new storyboard on the importance of data and analytics for businesses. Each of these downloadable articles explains how data and analytics solutions can help companies to make smart decisions, improve customer satisfaction, decrease e operational expenditure, reduce risks, and enhance fraud management.

Business leaders across industries are increasingly adopting big data analytics and data visualization techniques to improve their business operations. However, many organizations still seem to think of analytics as a quick fix for their business needs and investing in data and analytics is just the beginning of their journey. But to achieve business goals, it is high time for businesses to leverage data and analytics solutions that can help them boost transparency and enhance their approach towards data-driven decision making.

Quantzig’s data and analytics solutions have helped companies with the right data visualization techniques, capabilities, and frameworks to handle the volume, variety, and velocity of data to make informed business decisions while ensuring information privacy and security. Below, we have summarized some of Quantzig’s free resources and have also highlighted ways in which data and analytics solutions have helped businesses to gain a leading edge in today’s competitive business scenario.

Our data and analytics solutions help companies to make proactive business decisions and pre-emptive planning. Request a free proposal to gain better insights.

#1: How can analytics solutions transform business models? A successful business model is not just about completing a business plan or determining which product or service to pursue. It is about mapping out the strategy to create ongoing value for customers. But you must be wondering where to start. This free resource by Quantzig can be your key to success. It gives a detailed overview of how companies can reshape their business models by leveraging data and analytics solutions. Also, it unveils five secrets that can help companies identify and capitalize on new business opportunities.

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Gain a holistic view of your datasets with our customized data and analytics solutions. Request a FREE demo now!

#2: What are the top AI and analytics trends in 2019? Analyzing and optimizing the customer experience is the bedrock of successful digital transformation in 2019. Data and analytics capabilities with minimal manual efforts have become the hallmark of all business intelligence solutions. Artificial intelligence (AI) and machine learning technologies are transforming businesses and organizations have become highly dependent on automated data-analysis capabilities. This free resource by Quantzig uncovers some of the top AI and analytics trends that took off within corporate boardrooms but will continue to proliferate across different layers of business operations in 2019 and beyond.

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To know more about our portfolio of services, get in touch with our experts right away.

#3: What are the key steps to build an analytics-driven organization? Companies across industries agree that the capacity for data and analytics is becoming very crucial to their basic viability. Therefore, they need to be prepared for the future when data and analytics are going to be both important and integrated at all levels of organizational decision-making. It has become imperative for businesses to exploit available data in order to maximize profits. However, when it comes to extracting business value from data, most of the companies fail miserably. Quantzig’s free resource uncovers a few important steps that can help organizations to improve transparency, enhance business efficiency, and boost overall business performance. Download the free resource now to know more.

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data and analytics

Evaluating the Importance of Data Analytics and Visualization for Businesses

When it comes to successfully positioning your organization in the competitive market, data analytics and visualization act a key ingredient. Data visualization using appropriate data analysis methods can provide valuable insights into business operations. Such insights can be incorporated by businesses in the decision-making pipeline to make data-driven decisions. Leveraging such data analytics and visualization solutions can help companies to analyze their data irrespective of the size, scale, type, and domain and improve their decision-making capabilities.

Data analytics and visualization have become a necessity for companies to manage risks and comply with the changing regulatory landscape.

Therefore, it is imperative for businesses to realize the importance of data analytics and visualization as visuals are immensely capable of predicting all possible outcomes and make complex decisions to yield favorable outcomes. In this article, our team of experts has highlighted how data analytics and visualization techniques can be utilized to make the most of the statistical data, old experiences/learnings, and fresh ideas to launch new products.

Extracting insights from disparate datasets can be a difficult task for companies. But data analytics and visualization techniques can help. Request a FREE demo today!

How can data analytics and visualization help businesses?

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Data Mining and Analysis is Crucial to Your Business. Learn How!

What is data mining?

Data mining is an analytic process which is designed to inspect large amounts of data. It helps in searching systematic relationships and consistent patterns between variables. The final goal of big data mining is the prediction. In fact, predictive data mining is one of the most common types of data mining and has the most direct business applications. The process of big data mining basically comprises three stages:

  • The initial exploration
  • Model building or pattern identification with verification and validation
  • Deployment

Are you facing difficulty in multi-dimensional data aggregation and visualization? Get in touch with our experts to check out how our data mining and analysis solutions can help.

Benefits of data mining and analysis for businesses 

Fast and feasible decisions

Searching information from the huge amount of data is time-consuming. But data mining and analysis helps to get the information much faster eliminating the possibility of making mistakes and incorrect decision making. It also helps in comparing the fetched information with various factors, so the decisions become more authentic and reliable.

Build powerful strategies

Data mining and provides reliable information which further helps in making different strategies. In other words, by analyzing information in different dimensions it becomes easier to make effective strategies and implement them. This can help companies to effectively expand their business boundaries and make authentic decisions.

Actionable Insights

Want to know more about the benefits of data mining and analysis? Request for more info now!

Gain a competitive advantage

Data mining and analysis help in comparing own data with that of the competitors in different aspects. Competitive analysis is an important aspect of data mining that helps businesses gain a competitive advantage. 

Our latest success story showcases an excellent example of how data mining and analysis helped a leading company in building a successful predictive model to predict future outcomes. Read the complete story here.

What are the different data mining and analysis techniques?

Classification analysis

Classification analysis is a very important data mining and analysis technique which is used to retrieve relevant and important information about data, and metadata. It categorizes datasets in different classes. In classification analysis algorithms are applied to decide how new data should be classified. An excellent example of classification analysis would be our outlook email. In outlook, certain algorithms are used to characterize an email as legitimate or spam.

Association rule learning

Association rule learning method in the data mining and analysis process helps in identifying interesting relations between different variables in large databases. This technique helps in uncovering hidden patterns in the data that can be further used to determine variables within the data and the concurrence of frequently appearing variables in the dataset. This is one of the data mining techniques that is used for examining and forecasting customer behavior and is highly recommended in a detailed retail industry analysis.

Are you wondering how to segment the data and evaluate the probability of future events? We’d love to help. Request a free proposal now to know more about our portfolio of services.

Anomaly or outlier detection

This technique in the data mining and analysis process refers to the observation for data items in a dataset that do not match an expected behavior or an expected pattern. Anomalies are also known as novelties, outliers, noise, exceptions, and deviations. Often, they provide actionable and critical information. This is one of the data mining methods that can be used in a variety of domains, such as system health monitoring, intrusion detection, fault detection, detecting eco-system disturbances and event detection in sensor networks.

Clustering analysis

Cluster analysis in data mining and analysis process is actually a collection of data objects those objects are similar within the same cluster. That means the objects are similar to one another within the same group and are unrelated or dissimilar to the objects in other clusters. Clustering analysis is the method of data mining and analysis that help in discovering clusters and groups in the data in such a way that the degree of association between two objects is highest if they belong to the same group. The result of this analysis helps in creating customer profiles.

Regression analysis

Regression analysis is the data mining and analysis technique that helps to identify and analyze the relationship among different variables. It also aids in understanding the characteristic value of the dependent variable changes. This data mining method is generally used for prediction and forecasting.

We understand the challenges faced by companies when it comes to data visualization, data mining and analysis, reducing customer churn, and increasing customer loyalty. Our data mining and analysis techniques provide best-in-class frameworks to facilitate a better understanding of new business opportunities, competitive situations, and complex challenges. Request a FREE demo for more insights!

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Data Analytics Services are Crucial to Your Business. Learn Why and How!

Without data analytics services, business leaders are blind, wandering onto the web like a deer on a freeway.”

To have a good data management strategy into place, underpinning all business processes, is an apparent requirement for all business professionals. But it is tougher than you would think to get the data management process right. Almost every business has a need for data-driven insights today, but many are not yet realizing that ambition. Consequently, data management tends to get disintegrated and driven by multiple stakeholders. This results in high degree of disparate and inaccurate data for organizations and they face a number of challenges in maintaining it. Additionally, with the sheer volume of data, it has become very difficult for organizations to aggregate, manage, and create value from data. Therefore, businesses need to identify a more sophisticated approach to data visualization and the importance of good quality data. Right from building better relationships with customers to overcoming external and internal data visualization challenges, there is a need to revamp and evolve enterprise data management practices.

This is where data analytics services can help. If you are looking for ways to transform raw numbers into targeted solutions by gathering and analyzing day-to-day data within your company, it’s high time that you leverage data analytics services. Also, digital analytics can help you unveil hidden correlations by segmenting your market and customizing your products or services with the help of proper data frameworks. With data analytics services, a huge amount of unstructured data become concise and comprehensive data that are helpful in modeling and predicting your market opportunities. Whether you are in the healthcare, media and entertainment, insurance or chemical industry, data analytics services have become an essential requisite for survival. With that being said, let’s take a look at what is data analytics below and how it can help your business reach the pinnacle of growth.

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3 Data Modeling Best Practices to Boost Your Business Results

To solidify important business decisions with big data, it is important to understand data modeling. With new probabilities for businesses to easily access and analyze their data to boost performance, data modeling techniques are rapidly changing too. More than arbitrarily organizing data relationships and structures, data modeling must connect with end-user questions and requirements, as well as provide guidance to help ensure the right data is being used in the proper way for the desired results. In this article, we have explained some of the data modeling best practices that businesses must follow to improve their outcomes and save time.

Data Modeling Best Practices

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data and analytics

How Will Virtual Reality Transform Big Data Visualization?

Data is the new gold mine for any business. Modern companies are on the constant lookout for intelligent techniques and methods through which they can better analyze the data available to them. The traditional techniques of bar graphs and pie charts have almost become obsolete, especially as the volume of data is surging. Though there are a multitude of technological capabilities that enterprises have been using to retrieve meaningful outcome from the available data, the use of virtual reality in transforming big data visualization is a relatively new concept. The huge amount of data generated by a firm can be understood only through a series of analytic steps, and visualization plays a vital role in enhancing this strategy. Take the example of how VR technology solved Goodyear’s woe through data visualization. Goodyear, a popular tire manufacturer, wanted to know why they were losing races. The company built a complete simulation of its racing tires by looking at the entire historical data set.  With the help of simulation, it was possible to check the tires’ performance in real-time for minor adjustments.Free demo

Here are some of the other ways in which virtual reality can transform big data visualization :

Dynamic analysis of data

Seeing data life-size in front of your eyes is a more interesting and engaging method to understand data when compared to the traditional ways in which data analysis is carried out. Also, interactivity is the key to understand and handle big data properly. Data visualization through virtual reality can aid in interactivity and dynamic analysis of data because you can actually reach out and touch data. Interactivity further helps in comprehending and manipulating data.

Immersive data visualizationdata visualization

Immersive data visualization is the new buzz word among data scientists. This technique is a step ahead of 3D data and is used to perceive and manipulate data in VR. This technique is especially useful in the case of large datasets. There are specific tools to immerse data visualization through virtual reality, which when coupled with haptic or kinesthetic interfaces makes it possible to capture body language, human touch, and expression, making it an entirely different art and science.

Cross-referencing data

When data is put on paper or a digital screen, we often overlook certain details. But when there is access to data visualization through VR technology companies can capably stack relevant data, pair it and create visual cues that can be cross-referenced instantly and large amounts of data can be viewed at a glance. Virtual reality will also help analyze and fine-tune the understanding of the data to make it more efficient.

 Guide the subconscious minddata visualization

The human mind is truly incredible, but sometimes it becomes difficult to process vast amounts of information. One of the most exciting things that VR technology can do is to guide the subconscious mind. The immersive features of VR make it possible for it to understand the subconscious mind. And did you know that it is not just the body that gets tired, the brain also experiences fatigue? In such situations, the technology adapts itself to areas that make it easier for the user to understand and comprehend.

Multi-dimensional data analysis

Data visualization through virtual reality helps to view data in a multi-dimensional format, which means there is not just the use of hands but ears as well in comprehending data. This enables the viewer to analyze the subject, location, and significance of a particular data source.

Natural interactiondata visualization

We use our hands to feel things around us; virtual reality allows doing this through data visualization. Companies can manipulate data streams, push windows around, press buttons and practically walk around data worlds with the help of VR technology. Consequently, it enables users to make accurate data analysis and facilitates faster decision-making process.


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How Predictive Analytics is Driving the Future of the Connected Car Industry

The availability of a massive amount of data and exceptional mobile computing power has transformed the connected car technology. The traditional focus on vehicle management and infotainment systems has shifted towards developing the car’s ability to connect with the outside world. Multiple streams of communication such asFree demo IoT sensors, infotainment systems, and telematics systems in the connected car generate a colossal amount of data. Such datasets pave the way for the efficient use of predictive analytics tools to improve technologies associated with connected cars.

Ensure Passenger Safety

The AI system in a car has advanced to such a level that it can identify road signs, nearby cars, and road conditions to prevent a collision. The AI’s ability for collision prevention is augmented by employing predictive analytics in a connected car system. This can be possible by sharing vital information with nearby cars to warn each other when making abrupt maneuvers. Manufacturers are devising new ways to enhance collision avoidance systems by utilizing predictive analytics tools that utilize driver behavior data as an input.

Predictive Maintenance

The connected car system records and analyzes large data sets gathered from actuators, sensors, and machines. Such data sets can be useful in predicting requirement of full servicing, parts replacement, or other repair works. Apart from this, the data generated from connected cars can be shared with the manufacturer so that they can arrange logistics to deliver the spare parts to the required location by predicting its need.

Reinforcing Cyber Security

The idea of being able to control cars remotely may seem likely to invite security breach for malicious purpose and even terrorism. Predictive analytics is a powerful tool for identifying such cyber threats in its early stages. It utilizes user data, analyzes driver behavior to recognize patterns, and identifies behavior patterns that are inconsistent or different than the authorized user to stop unauthorized access.

Enter Quantzig:

Today, managers have access to a large stream of data, and decision-making on the basis of gut-feeling, the rule of thumb, and guessworks are largely eliminated with the advent of data analytics.

“Without big data analytics, companies are blind and deaf, wandering out onto the web like a deer on a freeway,” said a leading data analytics expert from Quantzig.

For more than 14 years, we have assisted our clients across the globe with end-to-end data management and analytics services to leverage their data for prudent decision making. Our firm has worked with 120+ clients, including 55+ Fortune 500 companies. At Quantzig, we firmly believe that the capabilities to harness maximum insights from the influx of continuous information around us is what will drive any organization’s competitive readiness and success. Our objective is to bring together the best combination of analysts and consultants to complement our clients with a shared need to discover and build those capabilities, and drive continuous business excellence.

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Can big data revitalize the oil and gas industry by increasing overall efficiency?

The oil and gas industry is facing major challenges as the cost of extraction is on the rise and current reserves are depleting gradually. The emergence of green energy is also questioning the sustainability aspect of oil and gas industry. In a bid to remain competitive in the energy market, oil and gas industry is turning towards big data analytics to supply a low-cost energy source to the people across the world. The concept of big data is quite familiar Free demoto the oil and gas industry players. Natural gas exploration, development, and production activities generate a large amount of data including a model image of Earth’s structure, oil flow rates and pressures, and machinery performance. Here’s a look at how big data can revolutionize the oil and gas industry:

Locating Oil Reservoirs

Oil reservoirs are located 5,000-35,000 feet below the Earth’s surface. Geologists and petrophysicists use 3D seismic data that provides the picture of Earth’s subsurface; thus, eliminating the need to drill a hole to explore the rock contents. Hundreds of gigabytes of seismic data are generated, which are then processed through algorithms that create an accurate picture of the Earth’s surface.

Increasing Process Efficiency

An increase in process efficiency can result in major cost savings in the oil and gas industry. One way of doing so is by generating accurate production forecasts to determine the output of the reservoir to allocate resources optimally. The other aspect concerns using big data to analyze data gathered from machinery to ensure uninterrupted workings and minimizing breakdowns. Such equipment is fitted with sensors to collect data on its performance, which can then be compared with aggregated data to improve machine efficiency.

Optimize Distribution Network

Big data is being used by oil and gas industry players to streamline the transport, refinement, and distribution of oil and gas. All data points such as production cost, economic indicators, and weather patterns are processed using complex algorithms to determine demand, allocate resources and set end consumer pricing.

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