We have heard enough about Big Data in the last few years. The technologies, the benefits, the big ideas etc. Now we are moving into the era of Application ie. how to realize the real benefits. Yes the Interprisers (Internet Companies) are in the fore front of using the various technologies and the data effectively since most of the current set of tools have their origins from these Interprising companies. The sucess of the current set of tools in the Interprises are because of the nature of the data they have to handle which is predominently unstructured. But when it comes to the real enterprises the challenge arises because of the nature of the data and the operations they perform on their data. The enterprise data are mostly structured and the operations performed on them are mostly relational. It does not mean Enterprises cannot benefit from using the Big Data technologies. The benefits a traditional enterprise would get using the current set of big data tools and technologies would not be same as what an Interprising company would be looking at. Hence enterprises need to have a different approach in using the technologies and tools. One of the key aspects will be looking at interoperability of the traditional big data tools sets like hadoop or nosql db’s etc with traditional Enterprise data management tools used for datawarehousing, ETL, BI related functions. Its critical that Enterprises have a clear principles to achieve the same.
Category: Big Data
Connected Devices Juggernaut
Google’s purchase price of 3+ billion for a start up that has a solution for Connected device is big considering that the solution is yet to prove its worth. Looking at the bigger picture connected devices and the information / data it will be generating is going to be a major area of focus in coming years. The path for success for companies focused in providing products/solutions is not going to be smooth. The reason for the same is the dependencies and challenges prevailing in the existing environment/ecosystem. Current solutions available out in the market are still a closed loop ones and proprietary. Including the Nest solution which Google has spent its monies for. As we have seen and has been proven again and again its critical to have an open platform and ecosystem for such technologies for mass adoption. Below are a list of challenges that i see is required to be addressed for the connected devices story to really take off.
1. Limitation related to connectivity. The solutions should make use of pervasive wireless technologies like the mobile networks rather than using fixed wireless technologies like WiFi or low range technologies like zigbee.
2. Identity and Authentication : There needs to be a programmable identity module framework that will help seamless connection to networks.
3. Data Privacy and Security : This has been a hot topic of the current internet services and would still prevail and be a strong barrier to data generated by connected devices. If we do not have a trusted model and framework for data sharing its hard to convince people of using such devices and sharing data.
4. Data Management (Collection, Management and Sharing) : Huge amounts of data are expected to be generated by connected devices. There needs to be solutions and services in place that can help collect such data, manage the data and help share the data.
5. Standards : Connected devices can be deployed by an enterprise, individual, government agencies for various purposes. The categorization and organization of such data in a standards based approach is critical. There are some standards based activity carried out by some organization and in certain technology areas. We need to have a single body to frame the end to end standards related to connected devices.
6. Cost and Revenue : One of the key barrier for connected devices is going to be the cost. One of the factors that will impact the same is the revenue model and the mass adaptability of the solution.
There is going to be a great potential for connected devices (imagine a petrol pump sensor alerts a user of low gas and the user immediately gets a phone alert with a google maps link to the nearest petrol pump with directions. To add on to this use case imagine if the back-end application that receives constant updates on the gas levels and based decides to send the notification based on the time of the day, gas pump distance from current location etc.). They key now is Organizations need to quickly address the various barriers that would hinder the adoption of connected devices.
Big Data – Expectations for this year
There has been a great push related to big data technologies and applications in the past years. Since most of these technologies have evolved from the Web and Social Media world there has been some challenges in applying the same in enterprise space for few key reasons. Enterprise data are mostly structured and since most of the current big data related technologies focus in resolving the handling of unstructured data it has been difficult for enterprises to come up with justifiable business case to use big data technologies. One of the use cases enterprise tend to look at is to get insights of their customers by combining the current structured data they own with the social media data of their customers. This also has its challenges since enterprises do not have information and access to their customers social media identity. Hence currently enterprises who are looking at big data technologies are purely looking to use it for the purpose of cost savings rather than using it for revenue generation. Hence I am looking forward to this year for companies to come out with technologies that enterprises can really use it for direct business benefits rather than it being just used as a infrastructure component to reduce costs.
One more area were is see lot of activities will be related to stream computing. Lot of moment has been generated last year with technologies like Storm, Spark , Splunk etc. I am looking forward to see how these technologies are going to be applied in enterprises. These technologies have great potentials to help enterprises in the real of real time decision making.
Sri Rajalingam 