Dataguise DgSecure Now Supporting Data Discovery for Amazon Redshift, RDS, and S3
LAS VEGAS, Nev., Nov. 30 — Dataguise, a technology leader in secure business execution, today announced that the Dataguise DgSecure solution for global sensitive data governance now supports sensitive data discovery on Amazon Redshift and Amazon RDS, as well as Amazon Simple Storage Service (S3). DgSecure helps data-driven enterprises move to the cloud with confidence by detecting, protecting, auditing, and monitoring sensitive information (e.g., PII, PHI, PCI data) across on-premises and cloud-based environments. With DgSecure, users organization-wide can tap into the data processing power and efficiencies of the AWS cloud to maximize the business value of their information while maintaining total ownership of all known and unknown sensitive data. The company will showcase the solution’s full suite of data security and compliance capabilities in booth 2424 at AWS re:Invent in Las Vegas, November 29 – December 1.
According to International Data Corporation (IDC), “More than 43% of organizations expect that within five years, the majority of their IT capability will be delivered through public cloud services, and that within three years, they will access 78% of IT resources through some form of cloud. New solutions born on the cloud and traditional solutions migrating to the cloud will steadily pull more customers and their data into cloud-based infrastructure.”
Dataguise DgSecure now scans for sensitive information stored on Amazon Redshift, RDS, and S3 and also provides ongoing monitoring of sensitive data in S3 throughout its lifecycle. The solution features transparent, role-based sensitive asset provisioning on the Amazon Elastic Map Reduce (Amazon EMR) platform so that users have access to sensitive data hosted in these environments through DgSecure role-based access policies.
“Many enterprises are moving to the cloud to take advantage of the reliability, scalability and agility provided by AWS,” said JT Sison, VP, Marketing and Business Development, Dataguise. “Dataguise customers leveraging Amazon Redshift, RDS, and S3 can benefit from our new offering and we look forward to sharing our stories of success with the thousands of attendees expected at re:Invent this year.”
During re:Invent 2016, Dataguise will activate its Five-Day Free Trial Program, providing prospective customers with full access to DgSecure software for a limited time. Organizations participating in the program will also receive up to $300 in AWS credits, along with instructions on how to implement DgSecure. For more information about DgSecure on Amazon Web Services, download the data sheet at http://bit.ly/2aTvulJ or http://amzn.to/2bdxGbp.
Dataguise is the leader in secure business execution, giving data-driven enterprises a simple, powerful solution for global sensitive data governance. DgSecure by Dataguise precisely detects, protects, audits, and monitors sensitive data across the enterprise, on premises and in the cloud. Delivering a single, dashboard view of sensitive data security, policies, access, and trends, DgSecure gives IT and business leaders the insights they need to manage risk and compliance while maximizing the value of information assets. The company is proud to secure the data of many Fortune 500 companies committed to responsible data stewardship. To learn more, visit: www.dataguise.com.
Dataguise Data Governance for Amazon Redshift, Amazon RDS, and Amazon S3
A river of news from Amazon, some pretty big stories from Hewlett Packard Enterprise, and a questionably valued Zillow listing near the North Pole are among the stories we didn’t get to this week. By Rich Freeman
As most folks are aware, the tryptophan in turkey doesn’t actually make you drowsy. Or at least it doesn’t make you any more drowsy than the tryptophan chicken has in even greater amounts. So what then explains the fact that more than a week after Thanksgiving, none of us here at ChannelPro can keep our eyes open long enough to write about so much of what’s going on in the technology industry? It’s a question we’d explore in greater depth if we didn’t feel another nap approaching.
Before it arrives, though, here’s a rundown of some stories we would have covered for you this week if we’d been awake a little more often.
So close yet so far. Somehow, despite all the gravy we ingested last week, your ChannelPro news team managed to make it to Las Vegas for the Ingram Micro ONE conference, and even file a few stories. Unfortunately, we didn’t manage to waddle over from that show to any of the three venues right up the street where Amazon Web Services was holding its massive re:Invent confab. And there was a lot going on at that event, it turns out.
Now this is where we’d congratulate ourselves for having prognosticated that artificial intelligence would figure significantly in the news from re:Invent, if not for the fact that it was kind of a no-brainer prediction given how many other serious players in IT have been talking about that topic lately. AWS did its best to one-up its peers, however, by announcing not one or two but three new AI services that developers can use to:
- Create conversational interfaces that allow users to control applications via voice and text commands.
- Equip applications to respond to those commands just as conversationally.
- Build image recognition capabilities into their cloud-based solutions.
And that, it turns out, was just a warmup. There were also seven new additions to the Amazon Elastic Compute Cloud, two new services for connecting the AWS platform to Internet of Things gizmos and other connected devices, a new SQL querying tool for the Amazon Simple Storage Service, and new compatibility between the Amazon’s Aurora database and the PostgreSQL open source database.
Sorry Support: Not Getting My Data
Recently, I made two interesting support requests, each to a different company. Both companies asked for the output of many different commands and log files. Both balked once I explained my organization’s security policy. The policy reads simply:
No anonymized data shall be delivered to a 3rd party.
It is a simple statement, but it has a powerful effect on all data being delivered to third parties, even for support. It implies that all user, machine, and service identifiers must be tokenized, encrypted, or outright removed. What must truly remain anonymous within our data? This is not simply a support question, but rather a major issue with all data today. Do we even know what is in our data? Do you?
I have built many anonymization scripts. Some have been generalized, and some have been specific to product logs and use cases. However, all of them have stripped out identifying information: information that is useful to hackers for attacking systems and accruing knowledge about users, and that exposes company and personal data. Most of this data is metadata—data about data—but it is extremely useful. It is useful to attackers, hackers, and all the bad guys. It is useful to any person or entity that just wants information, such as a surveillance state.
Data and data about data, metadata, need to be controlled, whether for support, data management, privacy, or intellectual property reasons. Every company needs to step up and add anonymization to any output that might be sent to a third party. However, this is just the tip of the iceberg. There are other reasons for data control to be put into place, and not just with regard to metadata—which in essence logs are about—but also with regard to real data.
This is the future of data services. Like network functions virtualization, I expect there to be data functions virtualization. We are already starting to see a data pipeline of sorts being created. Companies like Dataguise are there for protecting on ingest of data. Even the copy data solution Actifio is allowing a form of chaining to happen. It does not quite hook into enough functions, but it is a start. Orchestrating data functions is a part of any application today, but do data functions need to be in the application? As you scale up an application, this becomes an issue.
Data functions virtualization is the movement of discrete data services into a service chain for use by the application, perhaps by moving those services lower down, out of the application, perhaps into middleware or hardware. Some of those functions, such as encryption, compression, and deduplication, already reside in hardware. Others, such as tokenization, indexing, and masking, are higher up the stack. Still others are the basis for today’s analytics engines.
There is now a need to anonymize data, which can be done through tokenization, encryption, redacting, or removal of metadata about our data, PII, PHI, or PCI controlled data. As systems become more complex and more API driven, logs become even more important for debugging. Protecting your data should happen at all levels—not just within the data, but within the metadata as well.
Should data services be part of the application, or should they be part of something else?
In all cases, this is a serious question that needs some more thought. How would one implement data functions virtualization? Should the basics of data transformation, deduplication, compression, protection, or coalescing based on time be part of such data functions? Should these data services be part of data storage, the application, middleware, or all three?
We have been seeing data repositories grow. Now we need to consider how to best handle our data in the future, how to protect it, and how to transform it into more useful bits.
Anonymization is one such transformation. There are others. What do you need done to your data to make it safer to share, or more powerful for use? Do you have a data sharing and management policy?
Dataguise CTO Venkat Subramanian to Present on Sensitive Data Governance at Energy and Cyber Security Summit
DENVER, CO–(Marketwired – Nov 15, 2016) – Dataguise, a technology leader in secure business execution, today announced that Dataguise Chief Technology Officer Venkat Subramanian will present at the Energy and Cyber Security Summit Summit being held today in Denver. The presentation, titled Data-Centric Security for Energy/Utilities will focus on sensitive data governance best practices that ensure security and compliance for data-driven organizations.
The Energy and Cyber Security Summit is a day-long event aimed at providing the latest information on protecting data for electric utilities, oil and gas companies, energy industry integrators, Internet of Things developers, and any company with a connection to the electric grid. Also taking part in the 2016 event is the National Cyber Exchange and Secure Set Academy. The Summit will be held at Secure Set, 3801 Franklin St., from 8:30 a.m. to 7 p.m. MST.
As energy and utility companies optimize operations with data-driven IT infrastructures, there will be significant changes in the quantum of data being collected, moved, and accessed. While data is becoming a larger asset, it is also becoming a potential liability and causing concern for these operations. The primary challenge during such data-driven transitions will be data security and privacy. Additionally, there will be an increasing move away from data centers on premises and toward cloud environments. How can one reconcile across these transformations and maintain control over the data assets? The Dataguise presentation at the Energy and Cyber Security Summit will address such questions and detail how one securely leverages data for business.
Dataguise presentation specifics:
- WHO: Dataguise CTO, Venkat Subramanian
- WHAT: Presentation titled, Data-Centric Security for Energy/Utilities
- WHERE: Energy and Cyber-Security Summit
- WHEN: 11:30 am MST, November 15, 2016
“Data security is an important topic in the energy and utilities space as more suppliers employ operational and business analytics that involve customer data,” said Christine Shapard, Executive Director, Colorado Cleantech Industries Association. “Making sure the handling of this data is performed in a way that is secure and compliant with state and government mandates will be of importance to all in attendance.”
“The big-data nature of smart energy poses new challenges in data analytics and security that conventional security solutions cannot address,” said Venkat Subramanian, CTO, Dataguise. “Next-generation solutions are a must in these environments and we look forward to sharing our insights and technologies with the participating energy and utility providers.”
To learn more, download the data sheet on the company’s flagship solution, DgSecure 6.0, at http://www2.dataguise.com/l/74402/2016-09-26/6dkwvt.
Tweet This: @Dataguise to Present on Sensitive Data Governance at the Energy and Cyber Security Summit in Denver – http://bit.ly/1PzF3FJ
- Follow Dataguise on Twitter at: http://twitter.com/dataguise
- Follow Dataguise on LinkedIn at: http://www.linkedin.com/company/dataguise
- Follow Dataguise on Facebook at: http://www.facebook.com/dataguise
- Contact Dataguise directly at: http://www.dataguise.com/contact_us/
Dataguise is the leader in secure business execution, giving data-driven enterprises a simple, powerful solution for global sensitive data governance. DgSecure by Dataguise precisely detects, protects, audits, and monitors sensitive data across the enterprise, on premises and in the cloud. Delivering a single, dashboard view of sensitive data security, access, coverage, and trends, DgSecure gives IT and business leaders the insights they need to manage risk and compliance while maximizing the value of information assets. The company is proud to secure the data of many Fortune 500 companies committed to responsible data stewardship. To learn more, visit: www.dataguise.com
Safety First: The Best Use of the Public Cloud for Analytics Apps and Data
If concerns about data breaches have kept your organization from using the public cloud, read about use cases in which these worries should be a thing of the past.
A survey of European IT executives in 2014 revealed that 72% of businesses didn’t trust cloud vendors to obey data protection laws and regulations, and that 53% of respondents said the likelihood of a data breach increases due to the cloud.
In October 2015, Rob Enderle, president and principal analyst of the Enderle Group and previously Senior Research Fellow for Forrester Research and the Giga Information Group, wrote in a CIO.com post, “Simply stated, you can’t trust the employees of cloud service providers. Frankly, I don’t think we can really trust our own employees anymore either, but at least our capability to monitor them is far greater.”
This line of thought applies to big data and analytics as much as it does to transactional data, but for the purpose of this column, I am going to argue that there might be a place for the cloud in the production of analytics and analytics applications that will not trigger alarms in the minds of IT decision makers.
“Public clouds like Microsoft Azure and Amazon AWS have grown because companies understand the economics of using the cloud—but they still have major fears when it comes to the security of their data on public cloud platforms,” said JT Sison, vice president of marketing of Dataguise, which provides security solutions to protect sensitive data, no matter where that data is stored. “When you store your data internally, you have direct responsibility for all of your data, but when you use the cloud, this data security become a shared responsibility.”
Despite this understandable anxiety, companies shouldn’t give up on using public clouds in their big data strategies. Instead, they need to look at their data processing needs and determine the best places to deploy and to act on data for these various activities.
The data and applications activities that immediately stand out as candidates for the cloud are the development and testing of applications. In these cases, the test data that is prepared is not your production data, so there is less (and in many cases, no) risk of data breach or security exposure.
“Using a public cloud for application development and test is one of the best use cases that we see,” said Venkat Subramanian, Dataguise’s chief technology officer. “To assist companies so they can take advantage of the economics and the speed of the cloud in application development and test activities, we have intelligence that is built into our software that can detect and encrypt sensitive data before it is ever passed into the cloud. This enables applications to be tested in the cloud against realistic data, but not data that is in production or that has security sensitivities.”
To accomplish this level of security over data, the Dataguise software mashes data into usable but fictionalized data for application testing. “For example, if a company’s real customer lives in Chicago, the data might be mashed in the software to instead read Springfield, Illinois as the home residence of the customer,” said Subramanian. “Or, if the customer’s real first name is Mary, the software might change the name to Jane.”
The process seems simple enough. Most importantly, it has the ability to save enterprises many hours of preparing test data, or going through the process of having to refresh this test data when it begins to fail.
Techniques like this also meet IT’s most prominent objection to use of the cloud for any kind of sensitive data storage: The data is fictionalized to the point where it realistically functions in a test and development environment, but does nothing to satisfy the whims of a hacker.
20 Most Promising Big Data Companies for 2016
Redwood City, CA
Co-Founder & CEO
Automates data science for industrial IoT and provides predictive
| Fuzzy Logix|
| A predictive analytics software and services company that provides|
analytics tool for big data
| Shadan Malik,|
Provides easy-to-use, visually-appealing and cost-effective dashboard
| Ankit Goyal|
Co-Founder & CEO
For developing data strategy and architecture, the company offers
| Venkat N. Rajan,|
President & CEO
|Building Big Data assets for providing Richer, Finer, and Faster Analytics|
| SmartZip provides patent-pending predictive analytics, automated|
marketing campaigns and smart CRM follow-up tools for real estate
| TekLink International|
| Pankaj Gupta|
| TekLink International offers an onsite and offshore consulting practiced|
focussed on providing a cost effective Global Development Model
As Big Data Projects Grow, Security Concerns Do Too
Enthusiasm remains high for big data projects, but security concerns are raising their ugly head. A survey of 100 senior IT execs conducted by Gatepoint Research on behalf of data security tools provider Dataguise finds that two-fifths of respondents are ready to implement additional security for big data projects as part of an overall increase in IT security spending. While many have already deployed a wide range of security technologies, less than half are confident in their abilities to secure big data. Nearly three-fourths say security concerns thwart or delay big data initiatives. Delivering a managed security service optimized for big data creates new opportunities for solution providers. Most IT organizations have historically focused on network-perimeter and end-point security. With the rise of big data, they now need to secure terabytes, sometimes petabytes, of data stored in a variety of NoSQL databases. Unfortunately, not much thought is given to security until after a big data app is deployed. However, as more of these apps get deployed in production environment, it’s only a matter of time before hard questions about data security start getting asked.
Dataguise Publishes eBook on Unlocking the Benefits of Big Data
A new release out of the company reports, “Dataguise, a technology leader in secure business execution, today announced a new eBook titled Safely Unlock the Benefits of Big Data in the Cloud that is available for free download at http://bit.ly/29nT1dk. The eBook details how the Microsoft Azure platform and its cloud-based Hadoop service, Azure HDInsight, help solve the challenges associated with storing, processing, and analyzing big data. It also describes how the Dataguise DgSecure® solution supports a comprehensive strategy to provide precise sensitive data security and compliance for HDInsight service customers.”
The release goes on, “Apache Hadoop has dramatically reduced the complexities associated with how organizations process, store, and analyze huge volumes of structured and unstructured data. The economic benefits of storing and processing large data repositories such as Hadoop in the Cloud have proven to be increasingly compelling over the last few years. As a result, enterprises are turning to Microsoft Azure HDInsight to realize greater value from their big data projects. However, in order to conduct these operations without the risk of exposing sensitive data and falling out of compliance, it is necessary to leverage technology that continuously identifies, protects, and inspects data at a granular level to ensure secure business execution.”
It adds, “The newly published eBook by Dataguise provides guidance on achieving high levels of sensitive data protection in Azure HDInsight through five simple steps: (1) Understanding how data is collected, transferred, and stored across the extended enterprise. (2) Defining policies for what data elements are considered sensitive or subject to regulatory requirements (e.g., HIPAA, PCI, PHI, PII). (3) Discovering existing and continually detecting the existence of new sensitive data across all repositories. (4) Automatically encrypting or masking sensitive data according to administrative policies. (5) Viewing, monitoring, and alerting on sensitive data activities and risks in real time.”
Dataguise DgSecure 6.0 Now Available
Above the Trend Line: machine learning industry rumor central, is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items such as people movements, funding news, financial results, industry alignments, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz. Our intent is to provide our readers a one-stop source of late-breaking news to help keep you abreast of this fast-paced ecosystem. We’re working hard on your behalf with our extensive vendor network to give you all the latest happenings. Heard of something yourself? Tell us! Just e-mail me at: daniel
Our friends over at ClearDB, a pioneer in enterprise cloud database technologies, unveiled the launch of its Channel Partner Program. The new program allows partners to design and deliver a customized database as a service and extends the reach of ClearDB’s award winning Data Services Platform both nationally and globally. The program offers a simple on-boarding experience and allows partners to develop predictable and recurring revenue with an accelerated path to market. The ClearDB Channel Partner Program offers a premier partner experience that includes sales discounts and bundled service offerings along with access to technical resources, go to market development assistance and product training. Channel partners own the customer experience while receiving assistance from ClearDB, including guaranteed uptime service level agreements (SLA) and 24 x 7 support assistance … We just learned that Talena, the always-on big data pioneer, broadens its portfolio of big data platform support with Couchbase, one of the industry’s top NoSQL data platforms. Couchbase customers can now use Talena’s award-winning big data management platform to protect critical data assets at scale and iterate rapidly on applications, while realizing significant cost savings through built-in storage optimization and other efficiencies. The Couchbase integration and certification further extends the Talena software, which offers the industry’s broadest support for big data platforms …
In people movement news for the Big Data industry, we learned that MariaDB® Corporation, a popular developer’s choice for open source database technology, revealed the addition of Roger Bodamer and Cate Lochead to its executive team. Bodamer, Chief Product Officer, will lead the product, engineering, and strategy teams to deliver new capabilities that expand MariaDB support for emerging use cases. Lochead, Chief Marketing Officer, will be responsible for building a global brand to grow and accelerate sales … Rumor has it that Neustar, Inc. (NYSE: NSR), a trusted, neutral provider of real-time information services, announced that data science expert Venkat Achanta has been appointed Chief Data and Analytics Officer. In this newly created role, Achanta will be responsible for expanding Neustar’s authoritative identity and attribution platform to find innovative ways to create connected customer experiences across people, places and things. He will be based in San Francisco, California and report to Lisa Hook, Neustar’s President and Chief Executive Officer …
In new solutions news we found OpexLabs, a startup in the Container and Big Data technology domain, founded in August 2014, and located at Bangalore, India. HADOOP adoption is sluggish due to talent paucity and complexity of public cloud platforms. This is further aggravated by Hadoop distributors focusing only on developing features instead of simplifying the technology. OPEX LABS has simplified Hadoop adoption by launching a self-serving platform HAAS365. HAAS365 enables enterprises and data scientists to setup and experience Hadoop tools and distributions in just minutes with low risk … Dataguise, a technology leader in secure business execution, announced that Dataguise DgSecure® 6.0 is now available in the Amazon Web Services AWS Marketplace. DgSecure provides the ability to detect, protect, and monitor sensitive data as it lives and moves across on-premises and cloud-based repositories, including Amazon S3 via the Amazon Elastic MapReduce (Amazon EMR) platform. With DgSecure, data-driven enterprises can maintain total ownership of all sensitive data—known or unknown—in the cloud, enabling business users to embrace the power and efficiencies of cloud computing while minimizing data privacy and compliance concerns …
In customer wins news, Splice Machine, the dual-engine RDBMS for mixed operational and analytical workloads, powered by Hadoop and Spark, announced that Corax, a startup company that provides cloud-based cyber security operations, analysis and reporting software, has selected Splice Machine to manage its risk quantification calculations, store large data sets and meet future scalability requirements. Leveraging machine learning and a streamlined user interface, Corax will be able to provide faster, meaningful recommendations to its customers about cyber security actions, investment and insurance, helping them make decisions that prevent cyber crime and data loss … We also heard that Coho Data, a leading innovator and provider of true scale-out infrastructure solutions for enterprise private clouds, announced that DV Trading, LLC has deployed Coho Data’s high-performance rack-scale converged platform in their latest state-of-the-art trading infrastructure build-out. DV Trading is a North American-based proprietary trading firm with a significant presence on derivatives and securities exchanges worldwide. DV Trading actively participates in the marketplace both on a liquidity provisioning and global macro basis. The company selected Coho’s DataStream flash-optimized, data-centric storage platform to easily scale storage capacity and ensure high performance of financial applications …