PRINCIPLE 1. DESIGNING FOR COGNITIVE BUSINESS
With refererence to the article on COGNITIVE BUSINESS this is the first in a series of 3 communcations to share with you how a Cognitive Business journey may unfold. This article focusses on the themes of Analytics Acceleration and Data Centric Design.
As an introduction, here are 5 useful youtube clips to introduce you to the subject, A VIP Roundtable Discussion, Hybrid Cloud, Open Technology, Breaking the Silos and Placing Bets on Big Data.
a. Analytics Acceleration – IBM’s Vision for Cognitive Business
Deliver the fastest insights with infrastructure designed for complex analytics and machine learning.
If you could amplify the power of your brain, would you? How many people would turn down the ability to read a book in a few minutes and be able to comprehend, retain, and recall the information in an instant? What if you could compile all of the information in your brain and turn all of that knowledge into actionable insight?
Sounds like something out of science fiction.
Now imagine that you could capture, analyze, and store the accumulated information from your business. What if you had data points on the people, processes, systems, and machines that power your organization? And what if that data could help you make important real-time decisions? IBM is helping to make this futuristic vision a reality.
Think about this for a second, 80% of the world’s data is invisible to today’s technology. Cognitive infrastructure lets you act at the speed of thought.
Getting Actionable Business Intelligence Faster
You might be able to ask complex questions of your business data today. But how many people take part, how much data do you have to track down, and how long does it take to get complex answers?
Most business analytics tasks that were advanced by the standards of even a few years ago are now akin to sending someone to a gigantic library to look up books in a card catalogue, track them down, read them, and submit back a report.
The businesses that are leading today’s economy are interactive and agile. When IBM talks about building Cognitive Businesses and a Smarter Planet they aren’t just talking about empowering people to get answers from machines. They’re talking about powerful machines that learn, that interpret language, that provide deeper insight.
They’re talking about the business as a thinking organism, where every bit of data can be measured.
Giving Meaning to Unstructured Data
In a prescient quote from a 1963 text “Informal Sociology: A Casual Introduction to Sociological Thinking,” William Bruce Cameron wrote:
It would be nice if all of the data which sociologists require could be enumerated because then we could run them through IBM machines and draw charts as the economists do. However, not everything that can be counted counts, and not everything that counts can be counted.
We’ve reached an age where more than ever, everything can be counted. But to make it count, the data has to be given meaning and context. To give it meaning and context, it has to be arranged, sorted, and analyzed.
Large amounts of unstructured and dark data require high-performance technology to quickly provide meaning and insight.
Achieving Analytics Acceleration
So how do you tune your IT environment for the cognitive era? With the explosion of big data in the business world, you’re going to need technology that can understand, reason, and learn.This means:
- Investing in applications and database that help capture and process data.
- Servers, flash storage, and workload management designed for cognitive solutions.
- IT infrastructure that reduces data analysis from hours to milliseconds.
The Principles of Cognitive Business
You will hear more about concepts like data-centric design, open technologies, IT optimization, security, and controlled iteration at scale. This helps to tell the story of how to become a cognitive business. This isn’t a far-off future, IBM is already starting to help clients accelerate their journey to cognitive business.
b. What Is Data Centric Design?
Capture the largest volume and variety of data, and efficiently locate data and applications.
Having discussed how analytics acceleration helped to deliver faster insights using infrastructure designed for complex analytics, IT leaders need to become the architects of the future and employ a new data approach. IT leaders who are looking to make sure that IT plays a greater role in driving the business forward will architect environments that employ Data Centric Design.
Data Centric Design will help your organization capture the largest volume and variety of data. It will help you efficiently locate data and applications. It will help you make better business decisions faster. Sounds easy enough, but to make this a reality, you’ll need to make sure that your team is ready to focus on three key areas:
- Intelligent data management and placement
- Rapid data ingestion of diverse types and sources
- Moving analytics closer to the data
Where Is My Data? What Is Important?
To architect a data-centric design, you’ll need to consider your business drivers in addition to the data that helps to tell the story of those drivers. Sometimes that data isn’t readily available or available quickly enough to help drive decisions. Sometimes it isn’t even your data, but data from third parties. Consider these cases:
IBM Helps TBV Maximize Ad Revenue
TBV, a Hong Kong-based television broadcaster needed get a more precise ratings forecast to maximize ad revenue. To achieve this, they had to integrate external social media data with over 1 TB of data from its web and mobile applications each month.
The Data Centric Design: IBM Power Systems running DB2 with BLU Acceleration and Storwize v7000
IBM helps LSU use Hadoop to Analyze Genomics Workloads
Louisiana State University uses Hadoop to analyze over 3.2 terabytes of data. By investing in IBM compute and storage solutions, they were able to increase performance by 3x while using 2x fewer notes—a 9x improvement in terms of performance per server.
The Data Centric Design: IBM Data Engine for Hadoop and Spark—Power Systems, Spectrum Scale
Petrol Improves Sales with Historical Customer Data
Petrol and IBM worked to design a data centric solution that helped the European retailer use historical and transactional customer data to uncover new opportunities and improve sales. Petrol reduced data analysis of each new transaction from minutes to seconds. This allowed them to deliver new personalized cross-sell and up-sell promotions at the point of customer contact.
The Data Centric Design: z Systems with IDAA
The Future of Data Centric Design
To start moving toward data centric design means diving into the world of dark data, third party data, and your own data that you capture, but don’t capitalize on.
Consider this: Less than 1% of the data generated every day is mined for valuable insights.
Traditional data capture and analysis models are slowing progress. Data centric design is a new vision for computing that places the processing where the data is stored. Early adopters of this vision are in research laboratories and universities, but increasingly, businesses are tapping into their mountains of unstructured data to help them make business decisions.
IBM – Design for Cognitive Business
Analytics acceleration and data centric design are at the core of IBM’s Cognitive Business concept. You will hear more about how those foundational elements can help organizations build with collaborative innovation and deliver these solutions through cloud platforms.
IBM WHITE PAPERS :
(See attached file: Becoming a Cognitive Business with IBM Analytics - white paper.PDF)