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Ad Hoc Queries with Big Data or Small Data?

Here’s my view of Big versus Small with ad hoc analytics in either case

Do you think that you’re working with “Big Data”? or is it “Small Data”? If you’re asking ad hoc questions of your data, you’ll probably need something that supports “query-response” performance or, in other words, “near real-time”. We’re not talking about batch analytics, but more interactive / iterative analytics. Think NoSQL, or “near real-time Hadoop” with technologies like Impala. Here’s my view of Big versus Small with ad hoc analytics in either case.

Ad Hoc Analytics Small Data Big Data
Data Volume Megabytes – Gigabytes Terabytes (1-100TB)
Data Velocity Update in near real-time (seconds) Update in real-time (milliseconds)
Data Variety 1-6 unstructured data sources 6+ structured AND 6+ unstructured data sources
Data Models Aggregations with tens of tables Aggregations with 100s to 1000s of tables
Business Functions One line of business (e.g. sales) Several lines of business – to – 360 view
Business Intelligence Queries are simple, regarding basic transactional summaries/reports.

 

Example: retrieve a customer’s profile and summarize their overall standing based on current market values for all assets.

This is representative of the work performed when a business asks the question “What is my customer worth today?”

The transaction is a read-only transaction. Questions vary based on what business analyst needs to know interactively.

Queries can be as complex as with batch analytics, but generally are still read-only and processed against aggregates.

 

Queries span across business functions.

Example: retrieve a customer profile and summarize activities across all customer-touch points, calculating “Live-Time-Value” based on past & current activities.

This is representative of the work performed when a business asks the question “Who are my most profitable customers?”

Questions vary based on what business analyst needs to know interactively.

big-dog-little-dog

More on real-time analytics next…

Read the original blog entry...

More Stories By Jim Kaskade

Jim Kaskade currently leads Janrain, the category creator of Consumer Identity & Access Management (CIAM). We believe that your identity is the most important thing you own, and that your identity should not only be easy to use, but it should be safe to use when accessing your digital world. Janrain is an Identity Cloud servicing Global 3000 enterprises providing a consistent, seamless, and safe experience for end-users when they access their digital applications (web, mobile, or IoT).

Prior to Janrain, Jim was the VP & GM of Digital Applications at CSC. This line of business was over $1B in commercial revenue, including both consulting and delivery organizations and is focused on serving Fortune 1000 companies in the United States, Canada, Mexico, Peru, Chile, Argentina, and Brazil. Prior to this, Jim was the VP & GM of Big Data & Analytics at CSC. In his role, he led the fastest growing business at CSC, overseeing the development and implementation of innovative offerings that help clients convert data into revenue. Jim was also the CEO of Infochimps; Entrepreneur-in-Residence at PARC, a Xerox company; SVP, General Manager and Chief of Cloud at SIOS Technology; CEO at StackIQ; CEO of Eyespot; CEO of Integral Semi; and CEO of INCEP Technologies. Jim started his career at Teradata where he spent ten years in enterprise data warehousing, analytical applications, and business intelligence services designed to maximize the intrinsic value of data, servicing fortune 1000 companies in telecom, retail, and financial markets.

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