With the increase in Internet traffic and the amount of information in companies, the processing and storage of information is becoming an increasingly responsible and time-consuming task. Very often information is stored in an unstructured form. This means that the information does not have a predetermined data structure. As a rule, this is textual, graphical data or unordered tables.
Unstructured data is used in the following scenarios:
- speech recognition for customer identification in call centers
- image recognition in online stores
- text analysis of documents for further processing
- chatbots and natural language processing (NLP)
To understand how to handle unstructured data it's important to keep in mind that the most appropriate way for such data would be non-relational or NoSQL databases. Such data is more difficult to find and analyze. And once discovered, careful processing is required to evaluate applicability in business processes. Therefore, it is important for companies to develop strategies for working with unstructured data. The future commercial success of any company will depend on this.
You can have all the data in the world, but if you don't know how to use it for your business benefit, there's no point in sitting on that raw information and expect good things to happen.
The solution - Big Data Analytics - helps to gain valuable insights to give you the opportunity to make business decisions more effectively.
Data Analytics operation is divided into four big categories.
The purpose of descriptive analytics is to show the layers of available information and present it in a digestible and coherent form.
For example, you have the results of the marketing campaign for a certain period of time.
Depending on the model, the efficiency is calculated using goal actions like conversions, clicks, or views.
How insurance companies use big dataInsurance is one industry that has been in need of some memory-efficient solutions for some time now, considering the vast volumes of data a single insurance agency might accumulate and generate.
Big Data can be a real game-changer in this aspect.
Big Data Software MarketAccording to Market Research Future Analysis, the global Big Data Software Market is estimated to generate revenue of approximately USD 39 billion by 2023 growing at a CAGR of 13% during the forecast period 2017-2023.
Big data software’s are enterprise-class information technology platforms, providing features and functionalities for developing, deploying, operating and managing big data by patterns recognition, correlations, trends discovery, and other from huge datasets.
The global big data software market is anticipated to grow at a CAGR of 13 % during the review period of 2017 to 2023.Market ScenarioGrowing Big Data And Potential Applications Expanse Is Driving A Large MarketThe worldwide digital healthcare data reached a quantum figure of around 500 petabytes in 2012 alone and which is anticipated to reach 25,000 petabytes by 2020.The applications of big data include differentiating pricing strategies and price optimization, search engine optimization (SEO), advanced forecasting of patterns, better sample selection and others.
The business opportunities include quantification of the link between actions and revenues, higher market penetration, better customer targeting and engagement, economies of personalized medicine, real-time data for feedback and brand equity, corrective actions for customer switching, greater product differentiation, not to mention better customer satisfaction.Growth In Capacity And Capabilities In Technology Are Driving Greater AdoptionAdvances in database management and technology such as relational and parallel database architecture, development of data specific languages such as python, R and others are driving faster adoption as big data software’s are now capable of handling large and complex data sets.
Development of big data platform that blends traditional technologies suited for structured data, with new technologies designed to manage unstructured data address speed, flexibility, advanced analytics, ideal for data exploration, discovery, and unstructured analysis.
The increase in adoption of smart devices and the shift to digital technologies are significant drivers of market growth.Technology giants such as IBM (U.S.), Oracle (U.S.), Microsoft (U.S.), HPE (U.S.), SAP (Germany), Amazon Web Services (US), SAS Institute (U.S.), Dell Technologies (U.S.).
