Marriage between Big Data and Cloud Computing

Is Big Data Analytics right for your organization and is it the right timing? IDC says cloud spending will also rise by 25 percent to $100bn. “Data-optimized” platform-as-a-service (PaaS) products will become increasingly popular, IDC predicts, with Amazon Web Services taking a lead in providing various specialist solutions for businesses. With the Cloud Big Data Platform, you get a production-ready and performance-tested cluster, supported by a broad ecosystem of partners. A recent IDG Enterprise survey of enterprises and small and medium-sized businesses found that 60 percent and 46 percent of these firms said big data is a top priority, respectively.

The study discovered that a total of 70 percent of participants believe their cloud infrastructure investments will grow during the next three years. Another 52 percent of organizations anticipate similar expenditures to grow regarding data analytics, while 42 percent said the same for data mining and 36 percent for data visualization.

Cloud computing has become a viable, mainstream solution for data processing, storage and distribution, but the big data analytics and cloud computing don’t come with a silver bullet to fix bad data, dysfunctional organizational cultures, or automatically integrate with legacy applications. Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. The cloud model promotes availability and is composed of five essential characteristics: on-demand self-service, broad network access, resource pooling, rapid elasticity and measured service; three service models: Cloud Software as a Service (SaaS), Cloud Platform as a Service (PaaS) and Cloud Infrastructure as a Service (IaaS); and four deployment models: private cloud, community cloud, public cloud and hybrid cloud). The cloud computing model offers the promise of massive cost savings combined with increased IT agility. In addition, cloud computing democratizes big data – any enterprise can now work with unstructured data at a huge scale. In theory, managing cloud-based big data is cost-effective, scalable, and fast to build. Sticking data in Windows Azure Tables, Amazon SimpleDB, or MongoDB is just the start of the data science required to make the most of big data.


A survey by GigaSpaces found that 80 percent of IT executives who consider big data processing important are considering moving their big data analytics into the cloud. The two types of deployment models for cloud computing are public and private. These are offered for general purpose computing needs as opposed to specific types of cloud delivery models.


Big data is an inherent feature of the cloud and provides unprecedented opportunities to use both traditional, structured database information and business analytics with social networking, sensor network data, and far less structured multimedia. Big data applications require data-centric compute architecture, and many solutions include cloud-based APIs to interface with advanced columnar searches, machine learning algorithms, and advanced analytics such as computer vision, video analytics, and visualization tools. If organizations are managing a big data project that demands processing massive amounts of data, the private cloud might be the best choice in terms of latency and security.


Big data technology and cloud computing demand will push global IT spending beyond $2 trillions in 2014, according to IDC. Spending on big data technologies should see a 30 percent rise, with $14 billions expected to be shelled out on the analysis of huge pools of data such as customer behavior and business performance. High-volume big data cloud platforms will be in demand as firms look to gain significant business insight without the initial overhead costs of buying in physical infrastructure to handle the task. Gartner lists Amazon, AT&T, Google, HP, IBM and Microsoft among what it says are the top 10 cloud storage providers


Here’s the Big Data Institute’s (TBDI) Top 10 Big Data Trends in 2014:

  1. Big Data as a Service and Big Data Analytics will go mainstream
  2. More companies will implement Predictive Analytics, Machine Learning
  3. Data Science and Big Data Analytics will be embedded in BI for actionable Insights into Operational Reports and Executive Dashboards
  4. Cloud computing and Big Data will be tightly integrated with BI solutions
  5. Enterprise will be using big data techniques to secure IT infrastructure
  6. Hadoop will be used for operational system and transactional application
  7. Hadoop will be implemented as extensions to part of Enterprise Information Management solutions
  8. Big Data and Data Scientists skills shortage will grow as companies start ramping up hiring for big data and data science projects
  9. Rise in M&A activity in Big Data space with legacy BI companies acquiring niche big data vendors
  10. Companies will start new roles defined as Chief Data Scientists, Chief Data Officers and Chief Analytic Officer

The Cloud Computing model is a perfect match for big data since cloud computing provides unlimited resources on demand. Both cloud computing and big data appear to be at the top of the list of many IT executives. According to IDC the market for big data will reach $16.1 billion in 2014 growing 6 times faster than the overall IT industry. A Sierra Ventures survey of Fortune 500 CIOs and CTOs conducted in 2013 found that 32 percent cited mobile devices and big data as the top tech innovations influencing their companies, while 24 percent said the same regarding the use of the cloud. Are you prepared to deploy your Big Data in Cloud? If you would like to get started with Big Data analytics on the Cloud, take the course “Hadoop and the IBM SmartCloud Enterprise” available at no cost from Big Data University (