During Praveen's talk this past Tuesday he showed us a glimpse of the Paypal Here feature that, like Square, will allow payments to be taken using an iPhone or Android Phone. The two are very similar technologies. Square, which has been around since 2009 has a made a great first splash in the mobile payment business. Co-founded by Twitter's Jack Dorsey, they are now a billion dollar company and have the financial backing of Richard Branson (of Virgin fame). They are the current leader in the space, but are still relatively unknown by many. Enter Paypal! They are hoping to use their strong brand recognition to leap over Square in this mobile space. They are also slightly undercutting Square with a 2.7% transaction fee instead of 2.75%.
Another company to consider in the mobile payment space is Google with their Google Wallet via NFC. NFC or Near Field Communication is built into the mobile device and uses simply swipe their phone up against a compatible payment taking device from the retailer. Google is really pushing this technology, but the verdict is still up-in-the-air as to whether or not it will take off. Experts say that it could be up to 3 years before we know if this technology will be embraced by the public.
I personally do not use any forms of mobile payments at the moment, but it's nice to see that competition between all of these companies is making the landscape that much better for both the consumers and sellers using these offerings. Like the Blu-Ray and HD DVD battle of a few years ago, it will be interesting to see which company prevails.
Thursday, July 26, 2012
Tuesday, July 10, 2012
SQL vs. Non-SQL (Google Cloud Services)
After watching the Google I/O video on SQL vs. Non-SQL it
became clear that each service, while similar, offer unique differences that
help in deciding which one to use based on the business’s priorities. Those used to a more traditional DB setup
with SQL will find the Cloud SQL option more attractive. Those wanting more control over schema
changes and more scalability would probably be better off with the DataStore option.
Both of these technologies are built on Google’s cloud
services. Cloud services offer a number
of advantages:
- Fault Tolerance
- Low Maintenance
- Durability
- Accessibility
These cloud services great affect the way we interact with
the world. No longer are we dependent on
having that DB and Web Server combination in the basement of our house, or as
some VM Ware solution on some remote island somewhere. We now focus on our business and not focus on
the daily maintenance, setup, and running of these systems. Cost is another huge savings, we don’t need
resources to manage these systems, we can pay a flat-fee and rest the burden of
the system upkeep on someone else’s shoulders.
It’s really a whole new way of business that is the future of both the
internet from a commercial and consumer perspective. As a consumer that is going to a site that
uses these two cloud solutions, we can be assured of more up-time and possibly
lower costs as the cost savings of the company trickle down into the price of
their products or services.
Google’s “drive” for these services are more-than-likely
revenue driven. There is a huge amount
of revenue to be gained in this particular arena. More and more companies are realizing the
benefits of cloud services and Google wants to certainly gain some of this
market share. Google’s mantra seems to
be “get into anything and everything web” at this point and cloud services are
really just a piece of the pie. I think
it’s a smart move that could pay dividends down the road if they market and
manage the services properly. Google is
a trusted name with everything they do.
They put out quality services and applications so potential users of
this particular service can be rest assured that they are putting their
business into great hands.
I definitely believe that this functionality is “sound” and
has a place in IT and in business. As
stated earlier, many businesses are going to the cloud for a host of internet
related things. From software, to
storage, and platforms like Cloud SQL and DateStore. Businesses are realizing the true benefits of
using the cloud. Demand for cloud
services grows daily and having a trusted name like Google to help run their
business would seem like an attractive option for many companies. Though I have not personally used either the
Cloud SQL or DataStore products, it’s clear that they are both well thought out
products/services. Cloud SQL is built
upon MySQL, a trusted name in internet databases. It is also backed by the use of SQL, which is
a international standard for querying.
You get the benefits of Querying, Transactions, and Consistency with the
Cloud SQL service. DataStore, while
similar, is a different option for managing your DB needs. DataStore focuses more on Scalability,
Management, and Schema changes.
Depending on what type of business you are running, you could easily use
Cloud SQL on the front end, and then use the DataStore for archiving
purposes. They are two services that
complement each other well.
It seems like the key demographic for these services is
business. Business’s need DB’s to store
transactional data, and these toolsets are used just for that. No longer would they need to manage their own
DB Servers, they could rely on the cloud servers to do this for them. The Google I/O video mentioned the use of a
fictitious store called Greg’s List in which they could use both systems in
conjunction with one another. The Cloud
SQL could be used to store the active listings on the site and perform more
memory intensive transactions. Whereas
the DataStore could be used for archived listings an act as more of a disk
storage option. While you could get away
with just using one of the services, in this particular example it makes sense
to use both as each has their strength and weakness. Any type of business, whether it’s a mom and
pop website or a full blown Forture 500 company, has a need for this type of
cloud service.
Wednesday, March 28, 2012
BIG Data...
Some interesting facts...
So What is Big Data?
You may or may not have heard about Big Data before, but whether you like it or not you will probably run into it in the near future (especially if you are in IT). The world around us has exploded exponentially, and we must come up with a way to manage all of this large amount of data. The data will only increase over time with each year bringing exponentially more and more for us to manage.
Big Data consists of datasets that grow so large that they become awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing. I actually deal with large data sets at work (maybe not large enough to be considered Big Data, but large nonetheless). Sometimes I am working with spreadsheets of data that have millions and millions of records on it. I can understand how gangly and slow working with this data can seem. It takes forever to save these files, to pass them to others via some medium, and they are just cumbersome to analyze quickly. I'm not even working with truly Big Data, but I can imagine the need to managing these large datasets quickly and efficiently.
There are few key points regarding Big Data:
1) Big Data is showing up in all industries
2) Big Data can create value
3) Using Big Data effectively will become key for competition
4) There is a shortage of talent necessary to take advantage of big data
5) There are still obstacles to overcome before Big Data can be fully realized
6) Relational Databases are no longer needed
Point number 6 brings us to the next question...
What are "No SQL" databases?
These are data management systems that differ from the typical relational database model in that it doesn't use SQL as it's query language. These systems became popular from the likes of companies like Google, Amazon, Twitter, and Facebook who have to manage extremely large loads of data. These databases are built for speed and offer very little value other than data storage.
Why are these things important?
As I stated earlier, the world's data is growing at an exponential pace. There is a huge need to quickly manage all of this data. Being able to do such a thing puts a company way ahead of the curve. So in time it will all the company to make faster decisions on a whole host of different data elements. There is a shortage of professionals with big data experience, and it's only going to get worse as the data stores keep going up and up.
What is Hadoop?
Apache Hadoop is a software framework that supports data-intensive distributed applications under a free license. It enables applications to work with thousands of computational independent computers and petabytes of data. Hadoop was derived from Google's MapReduce and Google File System (GFS) papers.
Hadoop is a top-level Apache project being built and used by a global community of contributors, written in the Java programming language. Yahoo! has been the largest contributor to the project, and uses Hadoop extensively across its businesses.
What is Pig Latin and Hive?
Pig and Hive are two different methods for managing the Hadoop framework. Pig is more of a procedural language whereas Hive is more of a SQL type language. You could use one or the other or both with a Hadoop install. Hive was created by Facebook. Both are now owned by Apache (which also owns hadoop).
Why are these important?
These tools are important because they provide the user with easy and standardized methods for managing big data. They are also open-sourced tools so they are free to users.
Conclusion:
Big Data is here to stay and it's getting a lot of buzz lately. I'm going to start learning Hadoop so I can make myself more marketable. I mean, who doesn't want to put "Big Data Expert" on their resume...I know I do.
- It currently costs about $600 for a drive that would store all the music of the world
- 5 billion mobile phones in use in 2010
- 30 billion pieces of content shared on Facebook in a month
- 237 terabytes of data collected by the Library of Congress in April 2011
So What is Big Data?
You may or may not have heard about Big Data before, but whether you like it or not you will probably run into it in the near future (especially if you are in IT). The world around us has exploded exponentially, and we must come up with a way to manage all of this large amount of data. The data will only increase over time with each year bringing exponentially more and more for us to manage.
Big Data consists of datasets that grow so large that they become awkward to work with using on-hand database management tools. Difficulties include capture, storage, search, sharing, analytics, and visualizing. I actually deal with large data sets at work (maybe not large enough to be considered Big Data, but large nonetheless). Sometimes I am working with spreadsheets of data that have millions and millions of records on it. I can understand how gangly and slow working with this data can seem. It takes forever to save these files, to pass them to others via some medium, and they are just cumbersome to analyze quickly. I'm not even working with truly Big Data, but I can imagine the need to managing these large datasets quickly and efficiently.
There are few key points regarding Big Data:
1) Big Data is showing up in all industries
2) Big Data can create value
3) Using Big Data effectively will become key for competition
4) There is a shortage of talent necessary to take advantage of big data
5) There are still obstacles to overcome before Big Data can be fully realized
6) Relational Databases are no longer needed
Point number 6 brings us to the next question...
What are "No SQL" databases?
These are data management systems that differ from the typical relational database model in that it doesn't use SQL as it's query language. These systems became popular from the likes of companies like Google, Amazon, Twitter, and Facebook who have to manage extremely large loads of data. These databases are built for speed and offer very little value other than data storage.
Why are these things important?
As I stated earlier, the world's data is growing at an exponential pace. There is a huge need to quickly manage all of this data. Being able to do such a thing puts a company way ahead of the curve. So in time it will all the company to make faster decisions on a whole host of different data elements. There is a shortage of professionals with big data experience, and it's only going to get worse as the data stores keep going up and up.
What is Hadoop?
Apache Hadoop is a software framework that supports data-intensive distributed applications under a free license. It enables applications to work with thousands of computational independent computers and petabytes of data. Hadoop was derived from Google's MapReduce and Google File System (GFS) papers.
Hadoop is a top-level Apache project being built and used by a global community of contributors, written in the Java programming language. Yahoo! has been the largest contributor to the project, and uses Hadoop extensively across its businesses.
What is Pig Latin and Hive?
Pig and Hive are two different methods for managing the Hadoop framework. Pig is more of a procedural language whereas Hive is more of a SQL type language. You could use one or the other or both with a Hadoop install. Hive was created by Facebook. Both are now owned by Apache (which also owns hadoop).
Why are these important?
These tools are important because they provide the user with easy and standardized methods for managing big data. They are also open-sourced tools so they are free to users.
Conclusion:
Big Data is here to stay and it's getting a lot of buzz lately. I'm going to start learning Hadoop so I can make myself more marketable. I mean, who doesn't want to put "Big Data Expert" on their resume...I know I do.
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