Big Data Analysis

[vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column][vc_column_text]Although big data sounds like it belongs to the years of the rise of digitalization, this concept dates back to relational data in the 1970s. Data collection and processing, which used to be much more laborious and costly in the past, can be achieved at a much lower cost today. On the other hand, as technological developments regarding data accelerated, software-oriented business models also developed and became widespread. Big data directs the operations of many sectors from banking to transportation, social media to health. In this way, companies today utilise the power of data more effectively to capture new market opportunities by growing their market share. Considering that the Internet of Things and big data are affecting every aspect of our lives, it can be said that companies will invest more in this area in the coming years. We have compiled for you what you need to know about the definition of big data, the advantages it offers for companies and its future.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]

Data Analysis Methods and Autonomous Databases

[vc_column_text]The smallest unit of collected information is called data. Six different data analysis methods are the most frequently used worldwide. These are: A/B Testing, Data Fusion and Data Integration, Data Mining, Machine Learning, Natural Language Processing (NLP) and Statistics. A traditional database is a cloud-based solution that uses machine learning to automate management tasks. The most popular database models include: MySQL, Microsoft Access, Microsoft SQL Server, Oracle Database, Dbase, Firebird, FileMaker, MS Access. Autonomous, i.e. self-managed, databases are the newest type of database today and will be encountered more frequently in the future.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]

What is Big Data?

[vc_column_text]”Big data” is the process of making the masses of data collected over the Internet processable and meaningful through certain algorithms. Data is transformed from irregular piles into a whole of meaningful information by classifying it through artificial intelligence. In this way, it is possible to process data that cannot be stored, managed or analyzed with traditional database systems. The information obtained from the data is used in the functioning of many departments of the company.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]

Advantages of Big Data

[vc_column_text]The data obtained from search engines, social media, websites, document archives, log files, etc. are transformed into a kind of pool in the form of data sets with SQL and other software types, filtered, re-separated and classified, and thus transformed into meaningful information sets. The data analyses provided in this way are interpreted and form the basis for making more accurate decisions on behalf of organizations, carrying out business processes more effectively, and increasing efficiency and profitability in the operations of organizations. By analyzing and processing data, businesses gain more accurate information, gain rapid impact-response capability and thus gain greater flexibility and speed in regulating their operations.

In today’s conditions where the consumer is the focal point, companies gain advantages in determining consumer demands, meeting what is expected from the company or brand and providing innovations in line with customer demands, production increases and accelerates in many ways. Companies such as Amazon and Walmart are among the best users of big data and cloud technology. Global companies have doubled their sales by processing data collected from users, especially on social networking sites.[/vc_column_text][/vc_column][/vc_row][vc_row css=”.vc_custom_1629803910077{margin-bottom: 24px !important;}”][vc_column]

Use of Big Data in Various Sectors

[vc_column_text]Thanks to the use of big data, developments are being made in many sectors from health to banking, automotive to education. In the banking sector, big data analyses are used on many financial data, from customer account movements to money flow. On the other hand, many information such as how many times a mobile banking user uses mobile banking in a month, how often he/she performs which transactions with which clicks, spending habits and routines can be provided in the form of data. With the use of big data, banks can also develop data-based predictions on possible security threats and prevent them.

In the communication, media and entertainment sectors, big data is shaping the work carried out. Hundreds of categories of data such as which viewing habits are maintained on film and TV series platforms, which have entered our lives more with the Covid pandemic, which types of films are watched, how much they are watched, which scenes are fast-forwarded or how many times they are clicked are obtained. As a result of analyses and reporting, these data can direct the works created in film production, news and television broadcasting, game organizations and communication sectors. Although the issue of creating more watched productions and broadcasts in line with the data obtained from the audience creates discussions on the future of quality in the sector, it is inevitable to develop content based on big data. The role of big data in the development and growth of the content of Netflix, perhaps the best known of these platforms, is stated as an important example.

In the health sector, big data, which offers important opportunities such as early diagnosis, precautionary treatments, detection of possible problems, provides measures to prevent certain diseases before they occur. It also paves the way for academic studies and drug development, enabling health services to be provided at less cost, more efficiently and with better quality. In addition, big data provides many advantages in areas such as government services, insurance and retail. In these areas, big data analyses are used to prepare the necessary infrastructure for better quality service with continuity and equal opportunities. Demographic characteristics, personal data and movements reflected in consumption behaviors provide clear information to develop future predictions in big data analyses. With big data analytics, fast and reliable state services, municipal works, social and cultural activities and plans for the development of smart cities can be improved. Big data also provides more effective human resources; it provides an important basis for increasing efficiency in labor management, identifying potential problems and increasing potential. In this way, efficiency is obtained from the labor force more quickly and effectively.

The number of photos uploaded on the social media platform Facebook is over 5,000 per second, over 300000 per minute, around 20 million per hour and around 500 million per day. The masses of data on social media are used in many sectors and markets, especially in the communication and marketing sectors. Big data plays a major role in the strategic planning of efforts to ensure customer satisfaction and reputation, which is the ultimate corporate goal. In addition to measuring customer satisfaction, target audience expectations, perceptions and evaluations of the target audience are also provided from big data collected through feedbacks. Thanks to big data applications, businesses can plan how they can direct their marketing and communication activities in the future based on analyses and develop pinpoint efforts by predicting trends and possibilities. Businesses can organize their relations with all their interlocutors in both B2B and B2C business models and prevent possible crises and can prevent financial losses by creating procurement plans more accurately. In the light of analyzing big data and acting with a strategic communication focus, it becomes possible to carry out customer satisfaction or corporate reputation studies and other operational processes much more efficiently. For this reason, these investments of businesses are one of the most important requirements of the digital age in terms of getting ahead in the competitive environment.[/vc_column_text][/vc_column][/vc_row]