Tag Archives: cloud

Amazon re:Invent 2014 Recap: “Cloud has Become the New Normal”

It’s amazing how fast a year goes by. Last year, Informatica Cloud exhibited at Amazon re:Invent for the very first time where we showcased our connector for Amazon Redshift. At the time, customers were simply kicking the tires on Amazon’s newest cloud data warehousing service, and trying to learn where it might make sense to fit Amazon Redshift into their overall architecture. This year, it was clear that customers had adopted several AWS services and were truly “all-in” on the cloud. In the words of Andy Jassy, Senior VP of Amazon Web Services, “Cloud has become the new normal”.

During Day 1 of the keynote, Andy outlined several areas of growth across the AWS ecosystem such as a 137% YoY increase in data transfer to and from Amazon S3, and a 99% YoY increase in Amazon EC2 instance usage. On Day 2 of the keynote, Werner Vogels, CTO of Amazon made the case that there has never been a better time to build apps on AWS because of all the enterprise-grade features. Several customers came on stage during both keynotes to demonstrate their use of AWS:

  • Major League Baseball’s Statcast application consumed 17PB of raw data
  • Philips Healthcare used over a petabyte a month
  • Intuit revealed their plan to move the rest of their applications to AWS over the next few years
  • Johnson & Johnson outlined their use of Amazon’s Virtual Private Cloud (VPC) and referred to their use of hybrid cloud as the “borderless datacenter”
  • Omnifone illustrated how AWS has the network bandwidth required to deliver their hi-res audio offerings
  • The Weather Company scaled AWS across 4 regions to deliver 15 billion forecast publications a day

Informatica was also mentioned on stage by Andy Jassy as one of the premier ISVs that had built solutions on top of the AWS platform. Indeed, from having one connector in the AWS ecosystem last year (for Amazon Redshift), Informatica has released native connectors for Amazon DynamoDB, Elastic MapReduce (EMR), S3, Kinesis, and RDS.

With so many customers using AWS, it becomes hard for them to track their usage on a more granular level – this is especially true with enterprise companies using AWS because of the multitude of departments and business units using several AWS services. Informatica Cloud and Tableau developed a joint solution which was showcased at the Amazon re:Invent Partner Theater, where it was possible for an IT Operations individual to drill down into several dimensions to find out the answers they need around AWS usage and cost. IT Ops personnel can point out the relevant data points in their data model, such as availability zone, rate, and usage type, to name a few, and use Amazon Redshift as the cloud data warehouse to aggregate this data. Informatica Cloud’s Vibe Integration Packages combined with its native connectivity to Amazon Redshift and S3 allow the data model to be reflected as the correct set of tables in Redshift. Tableau’s robust visualization capabilities then allow users to drill down into the data model to extract whatever insights they require. Look for more to come from Informatica Cloud and Tableau on this joint solution in the upcoming weeks and months.

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Remembering Big Data Gravity – PART 2

I ended my previous blog wondering if awareness of Data Gravity should change our behavior. While Data Gravity adds Value to Big Data, I find that the application of the Value is under explained.

Exponential growth of data has naturally led us to want to categorize it into facts, relationships, entities, etc. This sounds very elementary. While this happens so quickly in our subconscious minds as humans, it takes significant effort to teach this to a machine.

A friend tweeted this to me last week: I paddled out today, now I look like a lobster. Since this tweet, Twitter has inundated my friend and me with promotions from Red Lobster. It is because the machine deconstructed the tweet: paddled <PROPULSION>, today <TIME>, like <PREFERENCE> and lobster <CRUSTACEANS>. While putting these together, the machine decided that the keyword was lobster. You and I both know that my friend was not talking about lobsters.

You may think that this maybe just a funny edge case. You can confuse any computer system if you try hard enough, right? Unfortunately, this isn’t an edge case. 140 characters has not just changed people’s tweets, it has changed how people talk on the web. More and more information is communicated in smaller and smaller amounts of language, and this trend is only going to continue.

When will the machine understand that “I look like a lobster” means I am sunburned?

I believe the reason that there are not hundreds of companies exploiting machine-learning techniques to generate a truly semantic web, is the lack of weighted edges in publicly available ontologies. Keep reading, it will all make sense in about 5 sentences. Lobster and Sunscreen are 7 hops away from each other in dbPedia – way too many to draw any correlation between the two. For that matter, any article in Wikipedia is connected to any other article within about 14 hops, and that’s the extreme. Completed unrelated concepts are often just a few hops from each other.

But by analyzing massive amounts of both written and spoken English text from articles, books, social media, and television, it is possible for a machine to automatically draw a correlation and create a weighted edge between the Lobsters and Sunscreen nodes that effectively short circuits the 7 hops necessary. Many organizations are dumping massive amounts of facts without weights into our repositories of total human knowledge because they are naïvely attempting to categorize everything without realizing that the repositories of human knowledge need to mimic how humans use knowledge.

For example – if you hear the name Babe Ruth, what is the first thing that pops to mind? Roman Catholics from Maryland born in the 1800s or Famous Baseball Player?

data gravityIf you look in Wikipedia today, he is categorized under 28 categories in Wikipedia, each of them with the same level of attachment. 1895 births | 1948 deaths | American League All-Stars | American League batting champions | American League ERA champions | American League home run champions | American League RBI champions | American people of German descent | American Roman Catholics | Babe Ruth | Baltimore Orioles (IL) players | Baseball players from Maryland | Boston Braves players | Boston Red Sox players | Brooklyn Dodgers coaches | Burials at Gate of Heaven Cemetery | Cancer deaths in New York | Deaths from esophageal cancer | Major League Baseball first base coaches | Major League Baseball left fielders | Major League Baseball pitchers | Major League Baseball players with retired numbers | Major League Baseball right fielders | National Baseball Hall of Fame inductees | New York Yankees players | Providence Grays (minor league) players | Sportspeople from Baltimore | Maryland | Vaudeville performers.

Now imagine how confused a machine would get when the distance of unweighted edges between nodes is used as a scoring mechanism for relevancy.

If I were to design an algorithm that uses weighted edges (on a scale of 1-5, with 5 being the highest), the same search would yield a much more obvious result.

data gravity1895 births [2]| 1948 deaths [2]| American League All-Stars [4]| American League batting champions [4]| American League ERA champions [4]| American League home run champions [4]| American League RBI champions [4]| American people of German descent [2]| American Roman Catholics [2]| Babe Ruth [5]| Baltimore Orioles (IL) players [4]| Baseball players from Maryland [3]| Boston Braves players [4]| Boston Red Sox players [5]| Brooklyn Dodgers coaches [4]| Burials at Gate of Heaven Cemetery [2]| Cancer deaths in New York [2]| Deaths from esophageal cancer [1]| Major League Baseball first base coaches [4]| Major League Baseball left fielders [3]| Major League Baseball pitchers [5]| Major League Baseball players with retired numbers [4]| Major League Baseball right fielders [3]| National Baseball Hall of Fame inductees [5]| New York Yankees players [5]| Providence Grays (minor league) players [3]| Sportspeople from Baltimore [1]| Maryland [1]| Vaudeville performers [1].

Now the machine starts to think more like a human. The above example forces us to ask ourselves the relevancy a.k.a. Value of the response. This is where I think Data Gravity’s becomes relevant.

You can contact me on twitter @bigdatabeat with your comments.

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Posted in Architects, Big Data, Cloud, Cloud Data Management, Data Aggregation, Data Archiving, Data Governance, General, Hadoop | Tagged , , , , , , | Leave a comment

Amazon Web Services and Informatica Deliver Data-Ready Cloud Computing Infrastructure for Every Business

At re:Invent 2014 in Las Vegas,  Informatica and AWS announced a broad strategic partnership to deliver data-ready cloud computing infrastructure to any type or size of business.

Informatica’s comprehensive portfolio across Informatica Cloud and PowerCenter solutions connect to multiple AWS Data Services including Amazon Redshift, RDS, DynamoDB, S3, EMR and Kinesis – the broadest pre-built connectivity available to AWS Data Services. Informatica and AWS offerings are pre-integrated, enabling customers to rapidly and cost-effectively implement data warehousing, large scale analytics, lift and shift, and other key use cases in cloud-first and hybrid IT environments. Now, any company can use Informatica’s portfolio to get a plug-and-play on-ramp to the cloud with AWS.

Economical and Flexible Path to the Cloud

As business information needs intensify and data environments become more complex, the combination of AWS and Informatica enables organizations to increase the flexibility and reduce the costs of their information infrastructures through:

  • More cost-effective data warehousing and analytics – Customers benefit from lower costs and increased agility when unlocking the value of their data with no on-premise data warehousing/analytics environment to design, deploy and manage.
  • Broad, easy connectivity to AWS – Customers gain full flexibility in integrating data from any Informatica-supported data source (the broadest set of sources supported by any integration vendor) through the use of pre-built connectors for AWS.
  • Seamless hybrid integration – Hybrid integration scenarios across Informatica PowerCenter and Informatica Cloud data integration deployments are able to connect seamlessly to AWS services.
  • Comprehensive use case coverage – Informatica solutions for data integration and warehousing, data archiving, data streaming and big data across cloud and on-premise applications mesh with AWS solutions such as RDS, Redshift, Kinesis, S3, DynamoDB, EMR and other AWS ecosystem services to drive new and rapid value for customers.

New Support for AWS Services

Informatica introduced a number of new Informatica Cloud integrations with AWS services, including connectors for Amazon DynamoDB, Amazon Elastic MapReduce (Amazon EMR) and Amazon Simple Storage Service (Amazon S3), to complement the existing connectors for Amazon Redshift and Amazon Relational Database Service (Amazon RDS).

Additionally, the latest Informatica PowerCenter release for Amazon Elastic Compute Cloud (Amazon EC2) includes support for:

  • PowerCenter Standard Edition and Data Quality Standard Edition
  • Scaling options – Grid, high availability, pushdown optimization, partitioning
  • Connectivity to Amazon RDS and Amazon Redshift
  • Domain and repository DB in Amazon RDS for current database PAM (policies and measures)

To learn more, try our 60-day free Informatica Cloud trial for Amazon Redshift.

If you’re in Vegas, please come by our booth at re:Invent, Nov. 11-14, in Booth #1031, Venetian / Sands, Hall.

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Big Data Driving Data Integration at the NIH

Big Data Driving Data Integration at the NIH

Big Data Driving Data Integration at the NIH

The National Institutes of Health announced new grants to develop big data technologies and strategies.

“The NIH multi-institute awards constitute an initial investment of nearly $32 million in fiscal year 2014 by NIH’s Big Data to Knowledge (BD2K) initiative and will support development of new software, tools and training to improve access to these data and the ability to make new discoveries using them, NIH said in its announcement of the funding.”

The grants will address issues around Big Data adoption, including:

  • Locating data and the appropriate software tools to access and analyze the information.
  • Lack of data standards, or low adoption of standards across the research community.
  • Insufficient polices to facilitate data sharing while protecting privacy.
  • Unwillingness to collaborate that limits the data’s usefulness in the research community.

Among the tasks funded is the creation of a “Perturbation Data Coordination and Integration Center.”  The center will provide support for data science research that focuses on interpreting and integrating data from different data types and databases.  In other words, it will make sure the data moves to where it should move, in order to provide access to information that’s needed by the research scientist.  Fundamentally, it’s data integration practices and technologies.

This is very interesting from the standpoint that the movement into big data systems often drives the reevaluation, or even new interest in data integration.  As the data becomes strategically important, the need to provide core integration services becomes even more important.

The project at the NIH will be interesting to watch, as it progresses.  These are the guys who come up with the new paths to us being healthier and living longer.  The use of Big Data provides the researchers with the advantage of having a better understanding of patterns of data, including:

  • Patterns of symptoms that lead to the diagnosis of specific diseases and ailments.  Doctors may get these data points one at a time.  When unstructured or structured data exists, researchers can find correlations, and thus provide better guidelines to physicians who see the patients.
  • Patterns of cures that are emerging around specific treatments.  The ability to determine what treatments are most effective, by looking at the data holistically.
  • Patterns of failure.  When the outcomes are less than desirable, what seems to be a common issue that can be identified and resolved?

Of course, the uses of big data technology are limitless, when considering the value of knowledge that can be derived from petabytes of data.  However, it’s one thing to have the data, and another to have access to it.

Data integration should always be systemic to all big data strategies, and the NIH clearly understands this to be the case.  Thus, they have funded data integration along with the expansion of their big data usage.

Most enterprises will follow much the same path in the next 2 to 5 years.  Information provides a strategic advantage to businesses.  In the case of the NIH, it’s information that can save lives.  Can’t get much more important than that.

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What is the Silver Lining in Cloud for Financial Services?

This was a great week of excitement and innovation here in San Francisco starting with the San Francisco Giants winning the National League Pennant for the 3rd time in 5 years on the same day Saleforce’s Dreamforce 2014 wrapped up their largest customer conference with over 140K+ attendees from all over the world talking about their new Customer Success Platform.

Salesforce has come a long way from their humble beginnings as the new kid on the cloud front for CRM. The integrated sales, marketing, support, collaboration, application, and analytics as part of the Salesforce Customer Success Platform exemplifies innovation and significant business value upside for various industries however I see it very promising for today’s financial services industry. However like any new business application, the value business gains from it are dependent in having the right data available for the business.

The reality is, SaaS adoption by financial institutions has not been as quick as other industries due to privacy concerns, regulations that govern what data can reside in public infrastructures, ability to customize to fit their business needs, cultural barriers within larger institutions that critical business applications must reside on-premise for control and management purposes, and the challenges of integrating data to and from existing systems with SaaS applications.  However, experts are optimistic that the industry may have turned the corner. Gartner (NYSE:IT) asserts more than 60 percent of banks worldwide will process the majority of their transactions in the cloud by 2016.  Let’s take a closer look at some of the challenges and what’s required to overcome these obstacles when adopting cloud solutions to power your business.

Challenge #1:  Integrating and sharing data between SaaS and on-premise must not be taken lightly

For most banks and insurance companies considering new SaaS based CRM, Marketing, and Support applications with solutions from Salesforce and others must consider the importance of migrating and sharing data between cloud and on-premise applications in their investment decisions.  Migrating existing customer, account, and transaction history data is often done by IT staff through the use of custom extracts, scripts, and manual data validations which can carry over invalid information from legacy systems making these new application investments useless in many cases.

For example, customer type descriptions from one or many existing systems may be correct in their respective databases however collapsing them into a common field in the target application seems easy to do. Unfortunately, these transformation rules can be complex and that complexity increases when dealing with tens if not hundreds of applications during the migration and synchronization phase. Having capable solutions to support the testing, development, quality management, validation, and delivery of existing data from old to new is not only good practice, but a proven way of avoiding costly workarounds and business pain in the future.

Challenge 2:  Managing and sharing a trusted source of shared business information across the enterprise.

As new SaaS applications are adopted, it is critical to understand how to best govern and synchronize common business information such as customer contact information (e.g. address, phone, email) across the enterprise. Most banks and insurance companies have multiple systems that create and update critical customer contact information, many of them which reside on-premise. For example, insurance customers who update contact information such as a phone number or email address while filing an insurance claim will often result in that claims specialist to enter/update only the claims system given the siloed nature of many traditional banking and insurance companies. This is the power of Master Data Management which is purposely designed to identify changes to master data including customer records in one or many systems, update the customer master record, and share that across other systems that house and require that update is essential for business continuity and success.

In conclusion, SaaS adoption will continue to grow in financial services and across other industries. The silver lining in the cloud is your data and the technology that supports the consumption and distribution of it across the enterprise. Banks and insurance companies investing in new SaaS solutions will operate in a hybrid environment made up of Cloud and core transaction systems that reside on-premise. Cloud adoption will continue to grow and to ensure investments yield value for businesses, it is important to invest in a capable and scalable data integration platform to integrate, govern, and share data in a hybrid eco-system. To learn more on how to deal with these challenges, click here and download a complimentary copy of the new “Salesforce Integration for Dummies”

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Informatica Cloud Powers a New Era in Cloud Analytics with Salesforce Wave Analytics Cloud at Dreamforce 2014

We are halfway through Dreamforce and it’s been an eventful and awesome couple of days so far. The biggest launch by far was the announcement of Wave, the Salesforce Analytics Cloud, Salesforce’s new entry into Cloud analytics and business intelligence. Informatica has been the integration leader for enterprise analytics for 20 years, and our leadership continues with Cloud analytics, as our Informatica Cloud portfolio is the only solution that Completes Salesforce Analytics Cloud for Big Data, fully enabling companies to use Salesforce Analytics Cloud to understand their customers like never before. But don’t take our word for it, view the Analytics Cloud Keynote from Dreamforce 2014, and see Alex Dayon uniquely call out Informatica as their key integration partner during his keynote.

DIY Great Customer Data

DIY Great Customer Data

The Informatica Cloud Portfolio delivers a broad set of analytics-centric services for the Salesforce Analytics Cloud, including bulk and real time application integration, data integration, data preparation, test data management, data quality and master data management (MDM) services. The portfolio is designed for high volume data sets from transactional applications such as SAP, cloud applications like Workday and new data sources such as Hadoop, Microsoft Azure and Amazon Web Services.

We have a great booth in the Analytics Zone, Moscone West, 3rd floor, where you can see demos of Informatica Cloud for Salesforce Wave Analytics and get lots more details from product experts.

And, you don’t need to wait till Dreamforce is over to try out Informatica Cloud for Salesforce Analytics. The free trial of Informatica Cloud, including Springbok, for Salesforce Analytics Cloud is available now. Trial users have unlimited usage of Informatica Cloud capabilities for Salesforce Analytics Cloud for 60 days, free of charge.

Aside from new product launches, and tons of partner activities going on, we’ve also got some great customers speaking at DF. Today, we have a great session on “Get Closer to Your Customers Using Agile Data Management with Salesforce” with executive speakers from BT, Dolby and Travel Corporation explaining how they achieve customer insight with use cases ranging from integrating 9 Salesforce orgs into a single business dashboard to unifying 30+ acquired travel brands into a single customer view.

On Monday, we had Qualcomm and Warranty Group present how their companies have moved to the Cloud using Salesforce and Informatica Cloud to meet the agility needs of their businesses while simultaneously resolving the challenges of data scaling, organization complexity and evolving technology strategy to make it all happen.

Win $10k from Informatica!

Win $10k from Informatica!

Drop by our main booth in Moscone North, N1216 to see live demos showcasing solutions for Customer Centricity, Salesforce Data Lifecycle and Analytics Cloud. If you want a preview of our Informatica Cloud solutions for the Salesforce ecosystem, click here.

During Dreamforce, we also announced a significant milestone for Informatica Cloud, which now processes over 100 Billion transactions per month, on behalf of our 3,000+ joint customers with Salesforce.

Oh, and one more thing we announced at DF: the Informatica Cloud Data Wizard, our next-generation data loader for Salesforce, that delivers a beautifully simple user experience, natively inside Salesforce for non-technical business analysts and admins to easily bring external data into Salesforce with a one-touch UI, really!

For more information on how you can connect with Informatica at Dreamforce 2014, get all the details at informaticacloud.com/dreamforce

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Embracing the Hybrid IT World through Cloud Integration

Embracing the Hybrid IT World through Cloud Integration

Embracing Hybrid IT through Cloud Integration

Being here at Oracle Open World, it’s hard not to think about Oracle’s broad scope in enterprise software and the huge influence it wields over our daily work. But even as all-encompassing as Oracle has become, the emergence of the cloud is making us equally reliant on a whole new class of complementary applications and services. During the early era of on-premise apps, different lines of businesses (LOBs) selected the leading application for CRM, ERP, HCM, and so on. In the cloud, it feels like we have come full circle to the point where best of breed cloud applications have been deployed across the enterprise, with the exception that the data models, services and operations are not under our direct control. As a result, Hybrid IT, and the ability to integrate major on-premises applications such as Oracle E-Business, PeopleSoft, and Siebel, to name a few with cloud applications such as Oracle Cloud Applications, Salesforce, Workday, Marketo, SAP Cloud Applications, and Microsoft Cloud Apps, has become one of businesses’ greatest imperatives and challenges.

With Informatica Cloud, we’ve long tracked the growth of the various cloud apps and its adoption in the enterprise. Common business patterns – such as opportunity-to-order, employee onboarding, data migration and business intelligence – that once took place solely on-premises are now being conducted both in the cloud and on-premises.

The fact is that we are well on our way to a world where our business needs are best met by a mix of on-premises and cloud applications. Regardless of what we do or make, we can no longer get away with just on-premises applications – or at least not for long.  As we become more reliant on cloud services, such as those offered by Oracle, Salesforce, SAP, NetSuite, Workday, we are embracing the reality of a new hybrid world, and the imperative for simpler integration it demands.

So, as the ground shifts beneath us, moving us toward the hybrid world, we, as business and IT users, are left standing with a choice: Continue to seek solutions in our existing on-premises integration stacks, or go beyond, to find them with the newer and simpler cloud solution. Let us briefly look at five business patterns we’ve been tracking.

One of the first things we’ve noticed with the hybrid environment is the incredible frequency with which data is moved back and forth between the on-premises and cloud environments. We call this the data integration pattern, and it is best represented by getting data, such as price list or inventory from Oracle E-Business into a cloud app so that the actual user of the cloud app can view the most updated information. Here the data (usually master data) is copied toserves a certain purpose. Data Integration also involves the typical needs of data to be transformed before it can be inserted or updated. The understanding of metadata and data models of the involved applications is key to do this effectively and repeatedly.

The second is the application integration pattern, or the real time transaction flow between your on-premises and cloud environment, where you have business processes and services that need to communicate with one another. Here, the data needs to be referenced in real time for a knowledge worker to take action.

The third, data warehousing in the cloud, is an emerging pattern that is gaining importance for both mid- and large-size companies. In this pattern, businesses are moving massive amounts of data in bulk from both on-premises and cloud sources into a cloud data warehouse, such as Amazon Redshift, for BI analysis.

The fourth, the Internet of Things (IOT) pattern, is also emerging and is becoming more important, especially as new technologies and products, such as Nest, enable us to push streaming data (sensor data, web logs, etc.) and combine them with other cloud and on-premises data sources into a cloud data store. Often the data is unstructured and hence it is critical for an integration platform to effectively deal with unstructured data.

The fifth and final pattern, API integration, is gaining prominence in the cloud. Here, an on-premise or cloud application exposes the data or service as an external API that can be consumed directly by applications or by a higher-level composite app in an orchestration.

While there are certainly different approaches to the challenges brought by Hybrid IT, cloud integration is often best-suited to solving them.

Here’s why.

First, while the integration problems are more or less similar to the on-premise world, the patterns now overlap between cloud and on-premise. Second, integration responsibility is now picked up at the edge, closer to the users, whom we call “citizen integrators”. Third, time to market and agility demands that any integration platform you work with can live up to your expectations of speed. There are no longer multiyear integration initiatives in the era of the cloud. Finally, the same values that made cloud application adoption attractive (such as time-to-value, manageability, low operational overhead) also apply to cloud integration.

One of the most important forces driving cloud adoption is the need for companies to put more power into hands of the business user.  These users often need to access data in other systems and they are quite comfortable going through the motions of doing so without actually being aware that they are performing integration. We call this class of users ‘Citizen Integrators’. For example, if a user uploads an excel file to Salesforce, it’s not something they would call as “integration”. It is an out-of-the-box action that is integrated with their user experience and is simple to use from a tooling point of view and oftentimes native within the application they are working with.

Cloud Integration Convergence is driving many integration use cases. The most common integration – such as employee onboarding – can span multiple integration patterns. It involves data integration, application integration and often data warehousing for business intelligence. If we agree that doing this in the cloud makes sense, the question is whether you need three different integration stacks in the cloud for each integration pattern. And even if you have three different stacks, what if an integration flow involves the comingling of multiple patterns? What we are noticing is a single Cloud Integration platform to address more and more of these use cases and also providing the tooling for both a Citizen Integrator as well as an experienced Integration Developer.

The bottom line is that in the new hybrid world we are seeing a convergence, where the industry is moving towards streamlined and lighter weight solutions that can handle multiple patterns with one platform.

The concept of Cloud Integration Convergence is an important one and we have built its imperatives into our products. With our cloud integration platform, we combine the ability to handle any integration pattern with an easy-to-use interface that empowers citizen integrators, and frees integration developers for more rigorous projects. And because we’re Informatica, we’ve designed it to work in tandem with PowerCenter, which means anything you’ve developed for PowerCenter can be leveraged for Informatica Cloud and vice versa thereby fulfilling Informatica’s promise of Map Once, Deploy Anywhere.

In closing, I invite you to visit us at the Informatica booth at Oracle Open World in booth #3512 in Moscone West. I’ll be there with some of my colleagues, and we would be happy to meet and talk with you about your experiences and challenges with the new Hybrid IT world.

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Once Again, Data Integration Proves Critical to Data Analytics

When it comes to cloud-based data analytics, a recent study by Ventana Research (as found in Loraine Lawson’s recent blog post) provides a few interesting data points.  The study reveals that 40 percent of respondents cited lowered costs as a top benefit, improved efficiency was a close second at 39 percent, and better communication and knowledge sharing also ranked highly at 34 percent.

Ventana Research also found that organizations cite a unique and more complex reason to avoid cloud analytics and BI.  Legacy integration work can be a major hindrance, particularly when BI tools are already integrated with other applications.  In other words, it’s the same old story:

You can’t make sense of data that you can’t see.

Data Integration Proves Critical to Data Analytics

Data Integration is Critical to Data Analytics

The ability to deal with existing legacy systems when moving to concepts such as big data or cloud-based analytics is critical to the success of any enterprise data analytics strategy.  However, most enterprises don’t focus on data integration as much as they should, and hope that they can solve the problems using ad-hoc approaches.

These approaches rarely work as well a they should, if at all.  Thus, any investment made in data analytics technology is often diminished because the BI tools or applications that leverage analytics can’t see all of the relevant data.  As a result, only part of the story is told by the available data, and those who leverage data analytics don’t rely on the information, and that means failure.

What’s frustrating to me about this issue is that the problem is easily solved.  Those in the enterprise charged with standing up data analytics should put a plan in place to integrate new and legacy systems.  As part of that plan, there should be a common understanding around business concepts/entities of a customer, sale, inventory, etc., and all of the data related to these concepts/entities must be visible to the data analytics engines and tools.  This requires a data integration strategy, and technology.

As enterprises embark on a new day of more advanced and valuable data analytics technology, largely built upon the cloud and big data, the data integration strategy should be systemic.  This means mapping a path for the data from the source legacy systems, to the views that the data analytics systems should include.  What’s more, this data should be in real operational time because data analytics loses value as the data becomes older and out-of-date.  We operate a in a real-time world now.

So, the work ahead requires planning to occur at both the conceptual and physical levels to define how data analytics will work for your enterprise.  This includes what you need to see, when you need to see it, and then mapping a path for the data back to the business-critical and, typically, legacy systems.  Data integration should be first and foremost when planning the strategy, technology, and deployments.

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Informatica’s Inclusion on the “R&D All-Stars: CNBC RQ 50″ Was No Accident

CNBC RQ 50Earlier this month, CNBC.com published its first ever R&D All-Stars: CNBC RQ 50, ranking the top 50 public companies by return on research and development investment. Coming in the top ten, and the first pure software play was Informatica, mentioned as first among great software companies like Google, Amazon, and Salesforce. CNBC.com is referencing a companion article by David Spiegel – Boring stocks that generate R&D heat-and profits. The article made an excellent point: When R&D productivity links R&D spending to corporate revenue growth and market value, it is a better gauge of the productivity of that spending.

Unlike other R&D lists or rankings, the RQ50 was less concerned with pure dollars than what the company actually did with it. The RQ50 measures increase in revenue as it relates to increase in R&D expenditures. Its methodology was provided by Professor Anne Marie Knott, of Washington University in St. Louis, who tracks and studies corporate R&D investment, and has found that the companies that regularly turn R&D into income typically place innovation at the forefront of the corporate mission and have a structure and culture that support it.

Informatica is on the list because its revenue gains between 2006 and 2013 correlate directly with its increased R&D investment over the same period. While the list specifically cites the 2013 figures, the result is due to a systematic and long-term strategic initiative to place innovation at the core of our business plan.

Informatica has innovated broadly across its product spectrum. I can personally speak to one area where it has invested smartly and made significant gains – Informatica Cloud. Informatica decided to make its initial investment in the cloud in 2006 and was early in the market with regards to cloud integration. In fact, back in 2006, very few of today’s well-known SaaS companies were even publicly traded. The most popular SaaS app today, Salesforce.com had revenues of just $309 million in FY2006 compared with over $4 billion in FY2014. Amazon EC2, one of the core services of Amazon Web Services (AWS) itself had only been announced in that year. Apart from EC2, Amazon only had six other services in 2006. In 2014, that number has ballooned to over 30.

In his article about the RQ50, Spiegel talks about how the companies on the list aren’t just listening to what customers want or need now. They’re also challenging themselves to come up with the things the market can use two or ten years into the future. In 2006, Informatica took the same approach with its initial investment in cloud integration.

For us, it started with an observation and then a commitment to the belief that we were at an inflection point with the cloud, and on the cusp of what was going to become a true megatrend that represented a huge opportunity for the integration industry. Informatica assembled a small, agile group made up of strong leaders with varying skills and experience pulled from different areas—sales, engineering, and product management — throughout the company. It also meant throwing away the traditional measures of success and identifying new and more appropriate metrics to benchmark our progress. And finally, it included partnering with like-minded companies like Salesforce and NetSuite initially, and later on with Amazon, and taking our core strength – on-premise data integration technology – and pivoting it into a new direction.

The result was the first iteration of the Informatica Cloud. It leveraged the fruit of our R&D investment – the Vibe Virtual Data Machine – to provide SaaS administrators and line of business IT with the ability to perform lightweight cloud integrations between their on-premise and cloud applications without the involvement of an integration developer. Subsequent work and innovation have continued along the same path, adding tools like drag-and-drop design interfaces and mapping wizards, with the end goal of giving line-of-business (LOB) IT, cloud application administrators and citizen integrators a single platform to perform all the integration patterns they require, on their timeline. Informatica Cloud has consistently delivered 2-3 releases every year, and is now already on Release 20. From originally starting out with Data Replication for Salesforce, the Cloud team added bigger and better functionality such as developing connectivity for over 100 applications and data protocols, opening up our integration services through REST APIs, going beyond integration by incorporating cloud master data management and cloud test data management capabilities, and most recently announcing optimized batch and real-time cloud integration under a single unified platform.

And it goes on to this day, with investments in new innovations and directions, like Informatica Project Springbok. With Project Springbok, we’re duplicating what we did with Informatica Cloud but this time for citizen integrators. We’re using our vast experiences working with customers and building cutting-edge technology IP over the last 20 years and enabling citizen integrators to harmonize data faster for better insights (and hopefully, less late nights writing spreadsheet formulas). What we do after Project Springbok is anyone’s guess, but wherever that is, it will be sure to put us on lists like the RQ 50 for some time to come.

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Informatica Cloud Summer ’14 Release Breaks Down Barriers with Unified Data Integration and Application Integration for Real Time and Bulk Patterns

This past week, Informatica Cloud marked an important milestone with the Summer 2014 release of the Informatica Cloud platform. This was the 20th Cloud release, and I am extremely proud of what our team has accomplished.

“SDL’s vision is to help our customers use data insights to create meaningful experiences, regardless of where or how the engagement occurs. It’s multilingual, multichannel and on a global scale. Being able to deliver the right information at the right time to the right customer with Informatica Cloud Summer 2014 is critical to our business and will continue to set us apart from our competition.”

– Paul Harris, Global Business Applications Director, SDL Pic

When I joined Informatica Cloud, I knew that it had the broadest cloud integration portfolio in the marketplace: leading data integration and analytic capabilities for bulk integration, comprehensive cloud master data management and test data management, and over a hundred connectors for cloud apps, enterprise systems and legacy data sources.. all delivered in a self-service design with point-and-click wizards for citizen integrators, without the need for complex and costly manual custom coding.

But, I also learned that our broad portfolio belies another structural advantage: because of Informatica Cloud’s unique, unified platform architecture, it has the ability to surface application (or real time) integration capabilities alongside its data integration capabilities with shared metadata across real time and batch workflows.

With the Summer 2014 release, we’ve brought our application integration capabilities to the forefront. We now provide the most-complete cloud app integration capability in the marketplace. With a design environment that’s meant not for just developers but also line of business IT, now app admins can also build real time process workflows that cut across on-premise and cloud and include built-in human workflows. And with the capability to translate these process workflows instantly into mobile apps for iPhone and Android mobile devices, we’re not just setting ourselves apart but also giving customers the unique capabilities they need for their increasingly mobile employees.

InformaticaCloud

Informatica Cloud Summer Release Webinar Replay

“Schneider’s strategic initiative to improve front-office performance relied on recording and measuring sales person engagement in real time on any mobile device or desktop. The enhanced real time cloud application integration features of Informatica Cloud Summer 2014 makes it all possible and was key to the success of a highly visible and transformative initiative.”

– Mark Nardella, Global Sales Process Director, Schneider Electric SE

With this release, we’re also giving customers the ability to create workflows around data sharing that mix and match batch and real time integration patterns. This is really important.  Because unlike the past, where you had to choose between batch and real time, in today’s world of on-premise, cloud-based, transactional and social data, you’re now more than ever having to deal with both real time interactions and the processing of large volumes of data. For example, let’s surmise a typical scenario these days at high-end retail stores. Using a clienteling iPad app, the sales rep looks up bulk purchase history and inventory availability data in SAP, confirms availability and delivery date, and then processes the customer’s order via real time integration with NetSuite. And if you ask any customer, having a single workflow to unify all of that for instant and actionable insights is a huge advantage.

“Our industry demands absolute efficiency, speed and trust when dealing with financial information, and the new cloud application integration feature in the latest release of Informatica Cloud will help us service our customers more effectively by delivering the data they require in a timely fashion. Keeping call-times to a minimum and improving customer satisfaction in real time.”

– Kimberly Jansen, Director CRM, Misys PLC

We’ve also included some exciting new Vibe Integration packages or VIPs. VIPs deliver pre-built business process mappings between front-office and back-office applications. The Summer 2014 release includes new bidirectional VIPs for Siebel to Salesforce and SAP to Salesforce that make it easier for customers to connect their Salesforce with these mission-critical business applications.

And lastly, but not least importantly, the release includes a critical upgrade to our API Framework that provides the Informatica Cloud iPaaS end-to-end support for connectivity to any company’s internal or external APIs. With the newly available API creation, definition and consumption patterns, developers or citizen integrators can now easily expose integrations as APIs and users can consume them via integration workflows or apps, without the need for any additional custom code.

The features and capabilities released this summer are available to all existing Informatica Cloud customers, and everyone else through our free 30-day trial offer.

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Posted in Big Data, Cloud, Cloud Application Integration, Cloud Computing, Cloud Data Integration, Data Integration, Uncategorized | Tagged , , , , , | Leave a comment