Five Predictions: Big Data in 2015


According to experts, in just a few years, Big Data technologies have gone from loud promises to one of the main driving forces behind the new digital era. In 2014, we increasingly saw how companies implemented projects more in big data from the test phase and moved their manufacturing operation.

This year, the organization will move from batch processing of big data to use them in real time. The current industry leaders and people who claim to be leaders in the near future, have made significant progress in the integration of new big data platforms in analytical systems that can process the information on the fly and respond quickly to changes in the business.

According to the research, 2015 will be dominated by five major trends.

1. Quick Update Of Data

The need for rapid updating of data is one of the main sources of Big Data technologies. Processes in legacy databases and data warehouses is slow, they are not flexible enough and are not satisfied with the business. In 2015, the speed of updating the data in organizations will be given more attention, but the emphasis will shift from data collection and data management to more active use of them.

Legacy databases and data warehouses are expensive, and solve the problems of generalization and structuring of data is necessary in attracting skilled database administrators. The need to involve database administrators leads to delays in access to new sources of data and the establishment of rigid structures that are difficult to change. Legacy databases are not flexible enough to meet the needs of most organizations today. Initial drafts of Big Data focused on the creation of storage for specific data sources.

Instead of increasing the volume of data at their disposal, the company will no longer engage in an assessment of their relevance and increasing efficiency of obtaining the required information. What capabilities of data analysis and operations are associated with their treatment, that organization has? How quickly information is updated when changing customer preferences, market conditions, competitive moves and features of operations? Answers to these questions will depend on the volume of investment and scale of projects in Big Data in 2015.

2. The Transition From The Lakes To The Data Processing Platforms

To a certain extent in 2014 the year of hubs, lakes or data (data lake) – repositories were considered, where the raw data was stored in the original format: structured, unstructured or semi-structured, ready for use. Value is determined by the presence of these lakes scalable infrastructure, highly efficient from an economic point of view due to the low cost of storing terabytes of data, and the ability to respond quickly to changing situations.

In 2015, the lake of data will continue to evolve. There will be new technologies that will accelerate the processing of data stored and perform various operations on them. This will not only improve the efficiency but also creates a single point of control, and a single point of security.

In 2015, the lake of data will be improved as we move from batch processing to real-time integration and file resources, Hadoop and database platform in large-scale processing. In other words, we are not talking about creating a large-scale data storage lakes that support complex queries and large reports, and on ensuring continuous access to the event processing and real-time data in order to promptly obtain the latest information and instantly take the necessary measures.

3. Self Service

Continuous improvement tools and Big Data services means that in 2015 the technical means will no longer be a bottleneck when accessing business users and analysts to the information they need.

In 2015, the technology will be introduced to enable business users to access the data of interest to them. Self-service systems to help developers and analysts to study the data directly. Before the creation of centralized data structures thought possible only with the participation of IT services. It was a very long and expensive process. Hadoop platform has allowed businesses in some scenarios to get easy access to the data structures in the performance of read operations. Leading organizations will implement data binding in the normal course of business and be able to receive information from a centralized structure. Self-service of this kind will help them use the new data sources and respond to emerging opportunities and emerging threats.

4. Consolidation of Hadoop Suppliers And New Business Models

In early 2013, Intel introduced its own distribution Hadoop, different from all others in that it is supported directly in Intel hardware. But a year later the corporation abandoned this idea and began to support the distribution in Cloud.

At the same time, Intel said that customers prefer to sit on the fence, watching how the market will develop Hadoop. Many different options offered by the suppliers, users resulted in confusion. In 2015 the consolidation of suppliers will continue Hadoop. Many will refuse to own distributions and try to focus on something else.

For 20 years, we use free software with open source software, which today represents great value for the market. Technology is improving gradually. Technological life cycle begins with the appearance of innovative ideas and create products, fundamentally different from the others, and ends when these products have completely lose their individuality. Edgar F. Codd invented the concept of relational databases in 1969. In 1986, the development of this innovative idea has turned into a public company Oracle, and conversion to mass production can be considered as the first release of MySQL version in 1995.

For database technology path from an innovative idea to mass product took 26 years. Hadoop was just entering a period of technological maturity. Since the publication of the first materials to Google MapReduce ten years ago. With the global spread of Hadoop we encountered in 10 years after the original concept. But Hadoop is still in the innovation phase, and offers vendors rashly adopting Red Hat for Hadoop, gradually withdraw from the market. This has already happened with Intel, and soon followed the example, Pivotal.

In 2015 we will see the evolution of a new, augmented by new nuances model software open source, in which deep innovations will be combined with the development of the forces of the community.

It is the community of software developers, open source play a key role in shaping the standards and seeking consensus. Competition has accelerated the transformation of the Hadoop processor batch analysis in a fully functional data processing platform.

5. From The More Advertising To Big With This

In 2015, the architects of corporate systems from a better understanding of Hadoop technology stack will move on to a more clear and specific definition of requirements for Big Data applications, including requirements for preparedness and business continuity.

If an organization is going as quickly as possible to move from experimentation to a serious introduction to the data center, it is necessary that the architects of corporate systems are in the forefront of the movement of Big Data. IT leaders have an essential role in determining the basic architectures, taking into account the requirements that apply to service-level agreements, the need to ensure high availability, business continuity and meet the critical needs of the enterprise. In 2014, the boom of Hadoop ecosystem marked by the proliferation of new applications, tools and components. In 2015, the market will focus on the differences between the platforms and architecture, which is necessary for the integration of Hadoop in the data center and achieve the desired results for the business.


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