The global healthcare industry is experiencing transformation due to the new regulatory laws and it is moving towards value based business. With growing demands of patients to improve quality of care and increased value, healthcare providers are under pressure to deliver better outcome. The rising cost dynamics of healthcare, increasing demands of patient, and new entrants are adding to complexities of healthcare business. (more…)
When working with clients or prospects, I always relished and appreciated an “Opportunity for Excellence“. What does that mean? It means that when a client or prospect calls with a specific problem that is time sensitive and we, as an organization and team, jump on the problem and work to solve it.
We have had several “Opportunities for Excellence” in the past few months’ with our clientele. On two of them we worked through the Christmas holidays. We have had numerous times where we had several of our colleagues pull “all-nighters” just to respond to a client’s needs. We have met deadlines, pushed ourselves, strived to turn out the best work we could do.
This excellence at my organization can only be exhibited by the members i.e. our employees. When will you have an “opportunity for excellence”? When will you be called upon to deliver success in impossible timeframes and conditions?
Let me end by telling you this. When you go the extra mile for your customer and succeed, you go from being a vendor to being a strategic partner.
Phil Hodsdon, SVP, Sales & Solutions at Bodhtree.
Shuffle and Sort – The input passed to every reducer is sorted by a key. The process of sorting and transforming the map outputs into reducer outputs is known as Shuffle.
The output produced by the mapper is not directly recorded onto the memory. This process involves buffering and processing data further to enhance efficiency. It is often a good idea to compress the map output while writing it onto a disk, as doing so improves performance, saves disk space, and optimizes the volume of data that is being transferred to the reducer. By default the output is not compressed, but it is easy to enable by setting the value of ‘mapred.compress.map.output’ to ‘True’.
The map output file resides on the local disk of the task tracker that runs the map task. This requires further processing by the task tracker that is about to run the reduce task for the partition. The reduce task requires the map output for a particular partition from several map tasks across the cluster. The map tasks may complete at different times and the reduce task starts copying their outputs as soon as each map task completes.
Bodhtree, a leader in ‘PACE’ technology IT Services, including Product Engineering, Analytics, Cloud Computing, and Enterprise Services. Bodhtree empowers innovative businesses strategies through a mission to Educate, Implement, Align, and Secure transformational technology solutions.
“Data will grow to several petabytes and zeta bytes in the next few years;” “Corporations will be overwhelmed by the sheer volume of data;” “By 2015 databases will grow so large that companies will have to rent space on the moon to store them.” These are just a few common quotes we hear from renowned industry analysts, experts and CIOs surrounding the topic of Big Data.
But for many observers, there’s still a lot of gray area surrounding when to apply Big Data solutions. How is Big Data different from traditional analysis tools? How does it impact an organization? Just because there are several terabytes of data, does that make it Big Data? Does it really matter?
We can make a generic bold statement here: Data is everywhere! When you pause to think, you’ll see it’s true. The cars we drive, stores we shop at, the phone we use, the websites we read, the social media we so closely embrace, the TV programs we watch, the election polls that we follow – everything generates data and it is all stored somewhere.
When it comes to Big Data, people commonly mention the 4 Vs, but this only scratches the surface. Traditionally, any large organization that implements ERP services has all these Vs associated with their everyday line of business. Admittedly, this is primarily “structured” data, and it can be handled by a traditional RDBMS or an MPP database. But in light of the other Vs, it technically has volume because everything is recorded in an ERP system; the incorrect and the correct entries alike form the millions and billions of rows. It undoubtedly has value; otherwise corporations would not bother to collect it. It clearly is volatile because data does not come at regular intervals. It also has variety; data comes in from multiple sources, such as CRM systems, HR systems and modules that are implemented within the organization.
Even if you add unstructured data, can you really derive strategic value for your business? What is this unstructured data comprised of? What kind of metrics can we extract from this unstructured data?
More often than not, Big Data buzz induces a cool factor akin to what was once associated with owning an iPhone/iPad or, back in the day, having a free Facebook account. Sometimes a personal agenda is associated with Big Data implementations. Several managers and CIOs have vested interests in showing off a ‘cutting edge’ Big Data implementation. We recommend organizations take a breather to make sure that the data problem they have qualifies as a Big Data problem.
…Stay tuned for a model CIOs can use to evaluate whether Big Data is the solution to their challenge…
Ajay Narayan is a presales solution architect for Bodhtree, a leader in data analytics and product engineering. Bodhtree partners with SAP and Informatica to assist companies in leveraging enterprise data to gain a competitive edge in the market. Bodhtree also offers the MIDAS product suite, which migrates, cleanses and integrates data between SalesForce, SAP and legacy platforms.