In the business world, having in-depth information about the customers’ interests is very important. Big Data Analytics is the process of examining customer data, and drawing conclusions using specialized systems and software. Big Data technologies are helpful for companies to make wise decisions while planning their business activities, and scientists and researchers to carry their works in right directions.
We at Scintillation Research provide our clients with comprehensive Big Data Analytics services helping them understand customer behavior, and implement the right business strategies. We offer:
We work with small, medium and big companies, and help them make right decisions that can bring more customers to them. We use advanced tools and technologies to provide business intelligence services, using which companies can easily discover diverse market parameters, thus launch only marketable products. In Business Intelligence, we cover-
Big Data studies comprises a wide range of reports comprising lots of data. Thus, it is difficult to study these reports manually, and fetch the useful information. This is where data mining software can be used. Using the data mining techniques, companies can have better understanding of their customers, their interests and demands, and design effective strategies and increase sales of their products. We prepare data mining reports using trending information sources such as Facebook, LinkedIn, Twitter, etc.
Machine Learning techniques are helpful when it comes to large scale data processing. The processes are carried out at high speed and drawing insights from mountains of data is easy. This allows companies to make more informed decisions, and focus on the areas their customers are more interested in. We believe that analyzing customers’ needs is the best way to grow in the competitive markets, and help our clients understand customer behavior and plan their business strategies accordingly.
We provide Big Data Analytics service in many sectors, and some are explained below:
In retail industry, we process the large amount of data from various sources to analyze the customer behavior (like which product in the market is more demanding, what is the pattern of customer purchases etc.). In addition, we analyze the trends other competitive industries in the same domain. Big data Analytics effectively analyzes large volumes of diverse data and helps companies gain a deeper understanding of customer demand. Applying retail Big Data through retail software solutions makes shopping more relevant, personalized and convenient, which can help you sell more and boost consumer loyalty.
The banking industry has evolved by leaps and bounds over the past decades, when it comes to operations and service delivery. But, most banks have failed to utilize the information within their own databases. However, that’s all about to change as the banking sector gears up to process immense volumes of data created and collected. Some industry experts expect a sevenfold increase in the volume of data, before 2020. Big Data Analytics is huge step towards the development of banking industries, and will propel it into the 21st century. Let’s have a look at big data’s advantages for the banking industry, and how it will make things easier.
In the healthcare sector, we analyze the data from various hospital to predict the chances of disease to patients, and patient reports. The volume, variety, and velocity of healthcare data is at an all-time high. Navigating all that information has the potential to transform your services. Join the key players in Big Data Analytics for healthcare and discuss the latest developments. Through thought provoking presentations, interactive sessions, and Q&A periods, take away strategies to:
Renewable energy technologies are quickly becoming popular globally as reliable sources of electricity. With a growing installed capacity of renewable energy plants comes a growing number of remote monitoring solutions to track the performance of these plants. Enormous amounts of data are being generated by these renewable energy plants and it is becoming important to create valuable insights from this data. Big Data Analytics performed on the data collected from these plants, enables owners and O&M crews to operate the renewable plants at the plants maximum potential. Among all the types of Big Data Analytics that could be performed on the plant data, predictive analytics holds the most promising of providing insights by leveraging performance data to create correlations and outcomes. We analyze the data of various sources like sensors, plants (solar, gas) to analyze and predict the future outcomes, like (How to increase power growth in solar industry, what would be the profit or loss, and analyzing the cost of the systems).
We use various tools to provide Big Data Analytics services. These tools are open source and free of cost available in the market:
It provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, etc.) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.
It is a free web analytics service offered by Google that tracks and reports website traffic. Google launched the service in November 2005 after acquiring Urchin. Google Analytics is now the most widely used web analytics service on the Internet. It is offered in two additional versions: the subscription-based Google Analytics 360, previously Google Analytics Premium, targeted at enterprise users, and Google Analytics for Mobile Apps, an SDK that allows gathering usage data from iOS and Android Apps.
It provides interactive visualizations with self-service Business Intelligence capabilities, where end users can create reports and dashboards by themselves, without having dependent on any information technology staff or database administrator. Power BI’s user interface is intuitive for those who are familiar with Excel and its deep integration with other Microsoft products makes it a versatile tool that requires very little upfront training.
If you have any question about Big Data Analytics, you can contact us.