Welcome to the era of Big Data.
By the end of 2017, analysts predict that the world will have created 20X more data in the last five years than in all of previous history combined. Numbers like that are hard to avoid, yet some companies still believe they can move forward with the same data strategies and technologies that were effective in the past. The reality is that companies need to learn how to live with Big Data, because it isn’t leaving any time soon. The need to analyze massive amounts of data in real-time will be a real-world requirement for a long time.
Whether you simply survive Big Data or thrive in it depends a lot on your data center. Today’s data centers need to adapt to Big Data’s requirements for scalability, flexibility and speed. In a sense, Big Data represents a perfect storm of data, where volume, variety and velocity converge. Enterprises need to prepare their data centers to withstand this storm, in essence building Big Data-survivable solutions.
So what would your data center’s Big Data Survivability score look like? Here’s a quick four-question quiz to give you a general idea (award yourself 25 points for each YES answer, with partial credit if you’re not 100% sure of the answer):
1. If I need an extra petabyte of storage, I can add it in under an hour.
Granted, most enterprises will never need to add so much data in so little time, but nearly all enterprises will need to re-think their scalability strategies with Big Data. Data is growing exponentially, and many enterprises will double their data volumes every two years. Fortunately, new solutions like HP’s StoreAll Storage systems can provide tremendous scale on a moment’s notice.
2. I can analyze raw data as it arrives without “cleaning” it first.
In the past, many companies ignored unstructured data. Today, it represents 80% of the data being generated and more companies have decided to leverage it through real-time analytics. Technologies such as in-memory databases and Apache Hadoop are helping make that possible, as are new analytics platforms designed for Big Data like HP Vertica.
3. I don’t need to hire a team of data scientists to make sense of my data.
The growing demand for Big Data expertise has led to a shortage of data “scientists” who can manipulate data to drive business innovation and revenue. While data scientists can bring a lot to the table in terms of added value, they shouldn’t be the sole connection between a business and its data. Companies that need data analytics expertise beyond their in-house capabilities should consider services partners like AdvizeX for expertise-on-demand throughout the year.
4. I can do all of the above with the budget I have today.
Data volumes and requirements may be growing exponentially, but IT budgets continue to grow incrementally if at all. CIOs need to find creative and cost-efficient solutions to the Big Data challenge, such as storage virtualization and hybrid Cloud architectures. These newer technologies can reduce the cost of data storage and access while improving performance, and enable CIOs to get a bigger data bang for their buck.
When you’re ready to get serious about Big Data, AdvizeX is there for you. ▪