Big Data is a field of study and practice that deals with the large amounts of data to which businesses are exposed every day – by analyzing and extracting meaningful and sensible information. Today, this term is associated with the use of predictive analytics, user behavior analytics, and other methods that obtain value from information.
Big Data
What is Big data?
What makes Big data really 'big'
In Big data, we consider data sets that are both large and too complex to be treated with traditional applications. Thanks to present-day consumers’ constant connection to the internet, and the continuous collection of information that occurs through devices and applications, businesses are often left with a very large volume of information. To create something useful from those sets, companies usually go through these steps:
- Defining a big data strategy, by specifying how they acquire, store, manage and use the data, and aligning the procedures with the business current and future goals.
- Considering the four Vs of big data and how they will impact on the company’s system. The Vs are: the volume of data, which refers to the size of data that needs to be analyzed and processed, the velocity, which describes the speed with which data is being generated, the variety of data, which is normally large and includes structured, semi structured and unstructured information, and the veracity, which denotes the quality of the data that is being analyzed.
- Collecting big data, that comes mainly from these two sources: streaming data obtained from the Internet of Things and connected devices (like smart cars, smart phones, industrial equipment, etc.), and social media data originating from users interactions on Facebook, Twitter, YouTube, etc. These two sources are in constant use and provide both useful and useless information, many times in unstructured form. Data can also be obtained from governments and world-level organizations that choose to share it, and other scattered sources like cloud data sources, suppliers, and customers.
- Storing the data in data warehouses or the cloud, making it available to access and manage.
- Analyzing the data with high-performance technologies according to the strategy and the indicators that are considered useful for this specific business.
Big data is commonly used to help businesses make intelligent decisions based on evidence, increasing predictability and profitability. Big data can power machine learning systems or any AI-based scenarios where learning is a necessity to make the program evolve.
What are the benefits of Big Data?
Big data is already being used in various industries and with many purposes, but new ways to apply this technology are being found every day. Here are some examples of how you can start today improving your business with big data:
- Big data can help you increase your business’ revenue, by improving decision making and customer service.
- It allows you to achieve enhanced operational productivity and reduce costs.
- The data received from social media, customer relationship management systems and other points of contact can help you greatly improve customer service, with more accurate response to client’s issues.
- Big data is a game changer in fraud detection, particularly when fed to machine learning algorithms that detect patterns and anomalies.
Big data scenarios
In elite sports, big data is being used to track athlete’s nutrition and sleep, and some teams are going as far as to monitor the player’s wellbeing through his use of social media. The NFL has developed a platform available to all teams, that helps in decision making based on the weather, the condition of the field’s grass, individual player’s statistics, etc.
Big data is even used to improve lifestyle, through the optimization of public structures and cities. By combining the information concerning traffic flow, weather data, and social media occurrences, in real time, utilities are being fine-tuned to extreme lengths. Traffic lights and signals, for example, can adapt to accommodate irregularities, minimize risk, and eliminate road traffic.
Things to note before using Big Data
Data quality is very disparate at the sources, and any big data analysis system should be able to address quality issues. This technology is currently on a fast-track mode and it is necessary to be careful before adopting Big data.
Big data @ Infogion
To take full advantage of Big data, you will need to hire a team experts, since it is too complex to handle in any any ordinary manner. At Infogion, we make sure that you are served by a top-level Big data team.