Big Data and Data Science

Big Data and Data Science

Big data is a term used to describe a holistic information management strategy that includes and integrates large volumes of both structured and unstructured data. These large sets of data are so big and complex that they cannot be analyzed with traditional data processing software. Big data trends refer to the use of predictive data analytics, user behavior analysis, and other advanced data analysis methods that extract value from data.

Data science is an interdisciplinary approach that uses scientific methods, processes, and systems to process data in various forms, either structured or unstructured and extract knowledge and insights. This concept unifies statistics, data analysis, and other methods and techniques borrowed from fields such as mathematics, statistics, information science, and computer science. More specifically, it draws from the subdomains of machine learning, classification, cluster analysis, data mining, databases, and visualization.

Big Data and Data Science Used for?

Companies are increasingly gathering data by using numerous devices. This data is then stored, sorted, processed, and analyzed so they can learn what customers prefer, how their business is performing, etc. The data can be put to almost any purpose, but it depends on the needs and goals of the organization and the abilities of the data scientist analyzing it.

Some uses of big data and data science include:

Best Understanding of Customers

One of the most common uses of big data analytics is to better understand customers and their behavior and preferences. Traditional data is being expanded with social media data, browser logs, text analytics, and sensor data to get a more comprehensive picture of their customers. Two places where data science is frequently used are digital marketing and advertising and ecommerce.

Optimization of Business Processes

Big data is also increasingly used for business processes optimization. Starting from retailers who optimize stock based on predictions generated from gathered data to general supply chain or delivery route optimization. Big data and data science give companies a deeper understanding of their everyday processes by providing specific quantitative measurements and deeper insights.

Image and Speech Recognition

Another way big data and data science are present in our lives is through image and speech recognition. One example are the tagging suggestions you receive when you upload an image on Facebook. This automatic tag suggestion feature uses a face recognition algorithm. Another example is Google’s “Search by image” option that allows you to upload an image and search for similar ones. Voice recognition is present in several popular products like Google Voice, Siri, Cortana.

Optimization of Machine and Device Performance

Using the advances in big data analysis, we can now make machines and devices smarter and more autonomous. Big data tools can be used to optimize the performance of computers and data warehouses. Google’s self-driving car and the Toyota Prius are using big data tools and are equipped with powerful computers, cameras, and sensors that enable them to safely drive without human intervention.

Science and Research

Using data in science and research is not new, but big data and data science tools are offering scientists new possibilities to tackle bigger sets of data and analyze them more thoroughly. Thus, use census and government collected data to create a bigger picture of health and social sciences, among other things.

Financial Trading

High-frequency trading (HFT) is an area where big data is greatly used today. Special big data algorithms are used to make trading decisions. The majority of equity trading is done by using computers which are programmed with complex data algorithms that scan markets for a set of specific customizable conditions and increasingly take into account signals from social media networks and news websites to search for trading opportunities and make buy and sell decisions in split seconds.

Advantages of Using Big Data and Data Science

The advantages of big data and data science do not necessarily come from the amount of data the company has, but how it utilizes it. The more the company uses the collected data, the easier it can find answers which will enable it to improve its efficiency, make time and cost savings, improve its services, etc.
Some of the biggest benefits of big data solutions and data science analytics are:

Cost Savings and Time Reductions

Big data tools, like Hadoop, can bring cost advantages to businesses when large amounts of data are stored since they help in identifying more efficient ways of doing business. Moreover, the high speed and in-memory analytics can easily identify new sources of data that can be added and analyzed immediately, and make quick decisions based on learnings, not guesses.

Product Development

By being able to gather customer behavior data, businesses can get a better understanding of customers purchase behavior and market conditions. They can follow the new and emerging trends on the market, identify customers’ needs and create products and services according to the needs of their target audience.

Ask and Answer More Questions, More Completely

Making business decisions relies on asking the right questions and finding answers that can help guide you in the right direction. Big data and data analytics solutions offer a way for companies to gather crucial business data and analyse it down to granular level. That way, asking and answering questions becomes a relatively straight-forward and drastically shortened process.