In the 1st Part of this 3 Part Post we tried to understand the question : What is Big Data?
However, we should not think that Big Data is just about bringing Social and Enterprise Data together. Big Data is rather about bringing together data that was otherwise too hard to catpure and hence left out or ignored or captured in an unstructured format as files(e.g. In the past the best record of this history was your Driving Record with the DMV which just tagged the number of accidents you had been in or the number of Traffic Violations you had made.
The DMV had no means of capturing all the Violations that never really got caught or noticed by a Cop. Today, it would be possible to collect a driving record of an individual based on a Real Time GPS location of the car simply based on a Mobile phone that you use! If DMV was to record this data every time you drove your car and make this your driving record with accurate details of Speed, Time, Distance Travelled. The Insurance firm could then correlate this data with the existing data on your Traffic Violations or Tickets and give you a much more accurate quote for insurance. In the future, they could also overlay this data on a GIS Map, Factor in Weather Conditions from a feed of data from the Meteorological Department and cut you some slack on your violations or speeding for the days you were in bad weather or simply going down a steep slope!
An Auto Insurance firm may do this in order to get more competitive than your current provider and hope that you would move to them. It can be hypothesised that there are bound to be inflection points which make it meaningful to embark on a Big Data journey for your enterprise before which it may not make sense to embark on Big Data and after which no matter what you spend your value from Big Data does not increase your Competitive Advantage. Increasingly, it should become evident to Enterprises that success in Big Data is all about success in the Cloud.
Special Thanks to Douglas Laney of Gartner for his foresight in the space of Big Data way back in 2001 and his insights on Volume and Variety of data. This is to interested CEOs and CIOs in India who visit this Blog, you can now read about the Cloud when flying at 36,000 feet in Air India. In Part 1 of this 3 part post we tried to understand if not answer the question: What is Big Data? The recent PRISM controversy highlighted, again, the legitimate concerns Independent Software Vendors (ISVs) have when it comes to storing sensitive data on the cloud.  But this week’s decision by Sony to pay a hefty ?250,000 fine imposed by the UK Information Commissioner’s Office for failing to protect against its 2011 PSN datacenter hacking, shows that a retreat to owned data center’s is not a solution either. We have always argued that the cloud is beyond hosting and by commoditizing building economies of scale it creates new opportunities for innovation and economic growth. But using the cloud to store data creates new challenges in how the data is being accessed and processed (security), ensuring that sensitive data is not available to third parties (privacy & confidentiality), and that legal data protection and other compliance requirements are met. Azure customers benefit from using security investment in Micorsoft’s own business (Office360, Dynamics) and AWS customers share the benefits of security investment in Amazons legendary e-retail operations.
This is platform-level security investment and in itself is not a panacea that will automatically deliver a secure app in the cloud.  The challenge for an ISV is to develop the security aspect in the new SaaS-based world within the team, realizing the transition to being an online service rather than a product that someone else will deploy and manage. This can be painful for traditional Enterprise Software vendors where deployment and its security is someone else’s (i.e.
Although cloud adds shared security investment and infrastructure, it does so at the expense of data sovereignty.  Data now resides on premises owned by someone else, the cloud operator, and is used in a multi-tenant manner.
Data confidentiality discussions tend to center around personal privacy, but there is a wide range of sensitive data ranging from financial information, meeting minutes, designs, confidential commercial documents, employee records, and personal data. The degree of confidentiality to all but personal data is normally self-regulated and subject to granular and often role-based access control determined by user requirements, other regulatory frameworks (UK Corporate Governance Code by the FRC, FCA, etc.) and organizational policies.
Personal data has an additional legal compliance layer as set by the UK Data Protection legislation.  The UK Information Commissioner’s Office, responsible for enforcing the law provides some good guidance on what constitutes personal data and what is required. Data subjects must be informed that their data is being collected and about how it will be used. Data subjects should be given the option to opt out of the collection and forward transfer of the data to third parties.
Private data can be transferred to third parties, only if the third parties follow adequate data protection principles. Data Controllers and Data Processors must make reasonable efforts to prevent loss or unauthorized access of private information.
Data Subjects must give access to information held about them, and the ability to correct or delete it if it is inaccurate.
Data Controllers and Data Processors must have in place effective means of enforcing these rules. The EU framework is considered more robust when compared to the “sectoral”  US approach towards . This provided assurances that if you stored your data in EU regions you complied with privacy legislation. However, last year’s EU study “Fighting cyber-crime and protecting privacy in the cloud” co-authored by Caspar Bowden former chief privacy advisor to Microsoft Europe, raised the alarm about an amendment known as Section 1881a of the FISA act which was extended until 2017.
Which means that unless companies like Goggle, Microsoft, or Amazon (or you if you have employees in the US) are prepared to see their employees go to prison, they will surrender the data.
It started becoming clear that Safe Harbor certification is an ineffective protection to FISA (but its compliance is still a good thing since it enforces a data protection ethos and compliance to third parties, except FISA). Arguably, one can say, this is only a small proportion of data.  The privacy legislation centers on the notion of a data subject being identifiable. A more traditional response is to retreat in search of a safe heaven in private “clouds” i.e. But even, if you decide to keep data and operations on-premise unless you are not online there are many risks from the increasing rise of hacking, cyber-crime, or cyber-activism that the Anonymous spite of attacks made headlines.  A retreat will most likely deprive you from the shared security investment the cloud operators have made and could leave you more vulnerable.
By trying to avoid FISA your data may end up in the hands of very unsavory groups.  If you think this is scaremongering, take look at this week’s headlines about Sony.
It is beyond the scope of this post to compare on-premise and cloud security, nor we are suggesting an always-cloud approach.  There is never a one-fit solution and both cloud and enterprise data centers have their place.
In this case, shielding your data is the only answer to the uncertainties of who can access and what can do with the data.

Faced with these dilemmas, planning for failure is the best way forward and data encryption is the core of planning for failure. Encrypting data both in motion (when loaded and being transmitted) and at rest provides a protection layer, which mitigates against intrusion and surveillance.  As long as those accessing your encrypted data do not have access to your encryption key, you can maintain strong data confidentiality. Encryption technologies have matured and encryption in motion is now a commonplace when using SSL, with e-Government, e-retail and on-line banking making it part of everyday consumer online experience. Driven largely by payment security compliance (PCI DSS), leading RDBMS such as Oracle and MS offer Transaparent Data Encryption (TDE) at column, table, and tablespace level, for their on premise products. AWS is beginning to address the area, too, with CloudHSM a managed Hardware Security Module (HSM) service with secure key storage and management. HMS and secure storage can also be an option that some chose to use to combine bootstrapping key retrieval from on-premise but that introduces single points of failure, security risks, and potential bottlenecks. Interest in homomorphic encryption is skyrocketing with DPARA investing  $20M in the homopmorphic-related PROCEED initiative with $4.7M already awarded to Galois Inc to extent its Cryptol toolset to be homomorphic. However, the consensus is that the full application of this technology is not ready for prime time yet.
This is where Israeli software house Porticor has an innovative application of homomorphic encryption.
Modeled around the Swiss-bank  key paradigm, the key is used to bootstrap a cloud VM appliance that you control and is then split with two parts encrypted. This is quite a promising product and we have spent some time evaluating it in our Rayhos labs. Understand the changing data security landscape and introduce security awareness in the product lifecycle using proven frameworks such as OWASP or MSDL. Don’t’ throw out the baby with the water; despite the limitations insist on EU data centers and Safe Harbor compliance.
Identify your privacy and compliance concerns and check the compliance aspect (including your user T & Cs) with a lawyer. Check your vendor’s response to the Cloud Security Alliance CCM on the STAR registry or use the CCM as the template to evaluate a vendor if they are not on the Registry.
Use an identity management system to have and manage granular, claims-based, standardized access control to data in a multi-tenant environment. Encrypt sensitive data from day one, even if key management is not bullet proof with minimum access control restrictions on key storage. So far EE has been the only network to offer 4G services, but its competitors now have the infrastructure in place and can also offer the benefits of high-speed internet. With operators urging business users to sign up to 4G and forgo the need for wired broadband, the mobile space is about to become more competitive. Vodafone –The operator is offering users an extra 4GB of data per month but only if they sign up before the end of October.
Three - Regardless of which iPhone 5s model users plump for, Three customers will have to pay an upfront fee of ?99. For the 16GB device, prices start at ?37 a month, with the most expensive plan setting back users ?41. The 64GB device will set users back ?47 a month on the cheapest plan, increasing to ?51 for people who opt for the most expensive one. If you want to get the 5S for an upfront cost of ?9.99, it’s going to cost you at least ?46 per month. So, ultimately we make it and here these list of best picture for your inspiration and information reason regarding the 223 5 56 Federal Lake City 5 56 Xm193 55 Grain Fmj 100 Round Bulk as exclusive updates collection.
Then in part 2 of this post we tried to understand the Issues with Data and the Evolution of Technology around Data.
Hence, Businesses will naturally push to gain better insights to improve their competitiveness. An Automobile Insurance Company in the future can offer you a highly competitive rate of insurance as compared to their competitor if they have sufficient data on your driving history. Or in order to increase the premiums of existing policy holders who continue to have a poor driving pattern even though they manage to avoid the cops and cameras!
This would mean a clear understanding of the Layers view of your business technology and how it you leverage Cloud within each of these layers and create the most cost efficient Big Data solution. Without his prior work it would have made my task of coming up with the concept and function of Crunchability a lot harder to Crunch! The paper is a sneak preview of the content you can expect in the Cloud Standards book when it is out this winter. In the past few months I have been talking to various CIOs and CEOs about the current state of the Cloud. In Part 2 of this post we shall try understand the Issues around Big Data or Data more broadly.
As, I write my first post on Big Data I can clearly see the need for a Book or maybe even a series of Books here that can help clear up the mist on Big Data.
If you already had an account, you may log in hereAlternatively, if you do not have an account yet you can create one here. In this post, we explore the data Security, Privacy, and Compliance (SPC) challenges of the cloud economy and highlight how encryption can be used to adopt a proactive approach to data SPC. With the ongoing cloud price war, the cloud is making cheap easy-to-access storage increasingly attractive, allowing ISVs to store and harness masses of data easily and focus on achieving competitive data intelligence, that only big players had access to. It puts at their disposal large amounts of investment cloud operators have put into their data centers.
For ISVs granular access control could be a multi-tenancy minefield and relying on declarative standardized access control frameworks helps. The framework relies heavily on three terms that you will find mentioned in many conversations – data subject  (the person whose data are being stored), data controller (who decides why and how data is collected, stored, and processed), data processor (anyone who processed the data on behalf of the data controller). This, combined with the emergence of US federal anti-terror legislation, notably the US Patriot Act, has led to early reservations on what level of data protection compliance is available from US-based vendors.

Most importantly it rules that transfers outside the EU must be very limited and subject to the provisions of the EU directive. Assuming you made technical decisions that didn’t accidentally land your data outside the EU data centers, you were not subject to the US Patriot Act. Until recently, and in additional to national identifiers (National Insurance Id, etc)- full name, post-code, and date of birth would be typically used to identify you, which should narrow the area of  data protection concern.  But this, in our opinion, could expose you to unforeseen breaches. This week Sony, dropped its appeal and will pay the fine, which also sent its shares tumbling in January with investors worrying about the real cost of the hack.
What we are saying is, that choice of a model should not be subject to simplifications, fear, and Faustian pacts of hacker exposure to avoid the complications of FISA. They are the direct result on an increasingly globalized, on-line, and inter-dependent world and getting fixated about the model avoids addressing the real issues. Google’s Eric Schmidt and Jared Cohen offer in their recent book “The Digital Age” a fascinating  futuristic extrapolation into the opportunities and vulnerabilities of a changing world.
But this rarely works and what is really needed is adjusting to realities and developing a proactive and robust approach to managing the risks. If operational and access security is defensive in nature aiming to prevent breaches, encryption compliments this by protecting data in the event of a breach.
In the cloud, AWS supports TDE for Oracle only whereas for Azure, IaaS installations of SQL Server support TDE – but SQL Azure does not.
The algorithm first introduced in a 2009 PhD thesis at Stanford University is fairly complicated but in a nutshell it allows you to operate on encrypted data without having to first unencrypt the data. Instead of trying to solve the entire homomorphic encryption challenge, it has applied the algorithm to a smaller sub-set of the problem, albeit a critical one, i.e. In the next installment we will go through a use-case and hands on example of using Big Data, Hadoop, AWS, and the Porticor’s offering. Cloud and on-premise are application delivery models, not ideologies; both subject to security threats.
Enterprise Software vendors moving to the SaaS world need to invest in operational security expertise.
This is an emerging area, and although you should not expect full and mature solutions, these vendors offer the building blocks for a data secure architecture.
Previously with Metastorm (now part of OpenText) he worked in a variety of roles – such as Chief Architect, Director of Product Development, and Head of Innovation – building development teams, shaping product and innovation strategy, and delivering award –winning products including social business process modelling on the cloud. If you’re opting for the 4G service, prices start at ?47 per month + ?79 upfront for the 16GB device. Those that plump for the latter plan will also benefit from 5,000 free minutes when making calls to other Three customers. This includes unlimited minutes and texts, 6GB of data along with a 6 month subscription to either Sky Sports Mobile or Spotify Premium.
However, Three is the only network to offer all-you-can eat data and has promised to upgrade customers to 4G without any additional charges. So, take your time and find out the best 223 5 56 Federal Lake City 5 56 Xm193 55 Grain Fmj 100 Round Bulk pics and pictures posted here that suitable with your needs and use it for your own collection and personal use.
Now in this 3rd and final part of the Post we try to understand the Importance of Big Data and why Businesses should care about Big Data. This data was too expensive to capture, hold and process or in simpler terms the technology did not exist at an affordable price. We shall also try and understand how technology has evolved around Data, Databases and what this means in the Big Data context.
Geoff gave an interesting perspective on how Facebook could be valued based on its potential market share of the Ad market and the projected growth of the market by 2015. It is believed that this happens because Blackholes have a high amount of gravity and hence pull in anything that is thrown towards them. The vendors submission to the Cloud Security Alliance’s STAR registry (in response to the Alliance’s Cloud Control Matrix) is a good place to have comparative feeling of how each one of them has invested in security. Incorporating, from day one, practices such as the OWASP guidelines (the OWASP Top 10 Project is a good practical starting point) and testing helps both understand the risks and plan how to address them with in-house and cloud vendor investment. Advances in machine learning and data analytics are changing what can identify you as a person with algorithms now being able to re-identify a person given large datasets, without requiring what we perceive as personally identifiable data items.
Some imply somewhat exaggerated claims resulting in PR fiascos in trying to remove StackExhange posts. In his new venture, John is working on Cloud, Agile Transformation, Big Data and Machine Learning projects.
This bundle includes unlimited calls and texts, six months of Sky Sports or Spotify and 6GB of data. Which can mean Better Products for Customers and Better Revenues and Profitability for the Enterprise. Am sure we have heard the terms Public Cloud, Private Cloud, Hybrid Cloud but maybe not Virtual Private Cloud.
He helps forward-looking companies develop product strategies, architectures, and teams that deliver business innovation and economic growth. 223 5 56 Federal Lake City 5 56 Xm193 55 Grain Fmj 100 Round Bulk pics and pictures selection that uploaded here was carefully picked and uploaded by admin after choosing the ones which are best among the others.
It is often argued that the Telcos stand to be the biggest gainers from the increased Internet Traffic and hence their desire to create new terms.

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