Hadoop, Big Data Analytics and Challenges Old Business Intelligence

It's not that old-school business intelligence software tools are going away, these upstarts grant. But both portray batch-oriented extract-transform-load (ETL) data integration, relational data warehousing, and old-school analytics as too slow, rigid, and expensive to keep up in the big-data era.

Hadoop is the future, because it's a massively scalable data-management and analysis environment that can handle variably structure data from many sources--log files, clickstreams, sensor data, social media sources and so on--without the delays inherent in dealing with the static schemas of relational databases.

If companies want to look at recent point-of-sale transactions alongside Web site clickstreams, recent online enrollments, email campaign results, and social media chatter, for example, it would be difficult if not impossible to quickly put all that data into a relational data warehouse and look for correlations.

Data-analysis and data visualization run on Hadoop. ETL and data warehousing and BI are just fine for the problem of looking at transactions here and there, but there's no chance of bringing it all together to look at the interactions across all of the islands of information.
Hadoop provides modules for data-integration (including connectors to mainframes, databases, social sources like Facebook and Twitter, and more), a spreadsheet-driven data-analysis environment, and a dashboarding and data-visualization environment.

Keys to the future of analytics and big data in healthcare

Increase Quality  and Drive costs down
From a cost perspective and a quality of care point of view, there are a number of different areas that will be impacted. For example, if a patient experiences an injury while staying in a facility, the organization isn't reimbursed for his/her care. So the ability for a system to see that this to happen and alert everyone, so that type of thing doesn't happen to me as a patient. The one way the US and Other government is putting pressure on that is you won't be compensated like the old days. They're going to tap into the information, and that's just one example. There are a whole bunch of things that could happen that are preventable and should be completely avoidable. After tapping into the information, That’s going to drive down the cost of healthcare.

Grow Physician-Patient Relationship
The physician-patient relationship will grow with the help of social media and mobile apps. And this all stems from the need for hospitals to keep patients healthy and out of their facilities. In the old days, hospitals made money, and the longer they keep patient there, the more they make. Analytics predicted that because of this, there will be an "explosion" of mobile applications and even social media, allowing patients to have easier access to nurses and physicians. It's about keeping patients healthy and driving down costs.

Quick ref. to BigData and Data Analytics

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Big Data Landscape

Source: http://blogs-images.forbes.com/davefeinleib/files/2012/07/Big-Data-Landscape-Jul-4-2012.00111.png

BIG DATA & BIG ENTERPRISES

For decades, companies have been making business decisions based on transactional data stored in relational databases. Beyond that critical data, however, is a potential treasure trove of non-traditional, less structured data: weblogs, social media, photographs etc. that can be mined for useful information. Decreases in the cost of both storage and compute power have made it feasible to collect this data - which would have been thrown away only a few years ago. As a result, more and more companies are looking to include non-traditional yet potentially very valuable data in their business intelligence analysis. Some of those big enterprises that have entered the world of Big Data with their flagship technologies/products are listed below:

·         IBM Big Insights - IBM Big Insights brings the power of Hadoop to the enterprise.

·         Microsoft HDInsight - HDInsight enables you to get up and running with your own Apache Hadoop cluster in Windows and Azure cloud in just minutes.

·         Oracle - Oracle offers the broadest and most integrated portfolio of products to help you acquire and organize these diverse data sources and analyzes them alongside your existing data to find new insights and capitalize on hidden relationships.

·         Google Big Query - Analyse Big Data in the cloud using SQL and get real-time business insights in seconds using Google BigQuery.

·         Hortonworks Data Platform (HDP) - Hortonworks Data Platform (HDP) combines the power and cost-effectiveness of Apache Hadoop with the advanced services and reliability required for enterprise deployments.

• Cloudera - Cloudera offers enterprises a powerful new data platform built on the popular Apache Hadoop open-source software package.

Big Data: The moving parts

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Daily data ... very big

Source: http://www.capgemini.com/technology-blog/files/2011/11/what_is_bigdata.jpg