The business world is changing. The dynamics of the client is changing. The customers are changing. And everyone is in a race to discover why instead of just who or how. Companies are in a competitive real-time struggle to know when customers buy something, where they buy it and what they are thinking before they even enter the store. Big data analytics services are young; it is not just data or technology, but all-social networks, customer behaviour and customer segmentation, to name a few. It is not possible to connect a big data application and expect to see the future. BI, master data management, big data and analytics must be integrated into a platform and grouped into a visually innovative solution. Data repositories, data mining and database technologies have existed in various forms for years. The exploration and analysis of semi-structured data without structure is something new. We did not analyse email messages, PDF files or videos few years ago. Internet was just a fad; distributed computing was not created yesterday, but the possibility of distributing and scaling a system in just a moment-and with smaller budgets-is new. In a similar way, wanting to predict the future is not a new concept, but being able to access all the data created and store them is something new. Various sources say that 90 percent of the data that exists today is only two years old. And those data are growing rapidly. If 90 percent of all data in the world were created in the last two years, what does that say about the data? Many companies have multiple databases and multiple database providers, with terabytes of data. Some of these systems accumulated data for 30 or 40 years. Many companies developed entire platforms for data warehousing and analytics from this old data. Large retail corporations became trillion dollar companies long before big data existed. Therefore, it was not the data that drove your business. However, data as a service can boost a company. Think of an online e-commerce products company. Now, people see them as a service platform, as service software, as big data services and as a data centre company in the cloud. E-commerce companies developed an incredible recommendation engine over the years from various open source technologies to scale its own databases and analytics. For data to be useful to users, they must integrate customers with financial and sales data, with product data, marketing data, social networks, demographic data, competitive data, and more. The integration of big data analytics services is not an easy task. Big data applications are one way to achieve this. It also requires time, patience and innovation. An open source system is much faster and less expensive to implement, but you need experienced personnel to do so. If you have no experience in working with big data, a big data provider application may be the best option, although this is more expensive. Remember that not everyone wants to be a software or hardware company. Sometimes developing an integrated big data platform requires a little development and purchasing to achieve your goals.
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