It’s no secret that the explosion of software-as-a-service (SaaS) apps has revolutionized the way businesses operate. From humble beginnings, the titans of SaaS today include companies such as Salesforce.com, NetSuite, Marketo, and Workday that have gone public and attained multi-billion dollar valuations. The success of these SaaS leaders has had a domino effect in adjacent areas of the cloud – infrastructure, databases, and analytics.
Amazon Web Services (AWS), which originally had only six services in 2006 with the launch of Amazon EC2, now has over 30 ranging from storage, relational databases, data warehousing, Big Data, and more. Salesforce.com’s Wave platform, Tableau Software, and Qlik have made great advances in the cloud analytics arena, to give better visibility to line-of-business users. And as SaaS applications embrace new software design paradigms that extend their functionality, application performance monitoring (APM) analytics has emerged as a specialized field from vendors such as New Relic and AppDynamics.
So, how exactly did the growth of SaaS contribute to these adjacent sectors taking off?
The growth of SaaS coincided with the growth of powerful smartphones and tablets. Seeing this form factor as important to the end user, SaaS companies rushed to produce mobile apps that offered core functionality on their mobile device. Measuring adoption of these mobile apps was necessary to ensure that future releases met all the needs of the end user. Mobile apps contain a ton of information such as app responsiveness, features utilized, and data consumed. As always, there were several types of users, with some preferring a laptop form factor over a smartphone or tablet. With the ever increasing number of data points to measure within a SaaS app, the area of application performance monitoring analytics really took off.
Simultaneously, the growth of the SaaS titans cemented their reputation as not just applications for a certain line-of-business, but into full-fledged platforms. This growth emboldened a number of SaaS startups to develop apps that solved specialized or even vertical business problems in healthcare, warranty-and-repair, quote-to-cash, and banking. To get started quickly and scale rapidly, these startups leveraged AWS and its plethora of services.
The final sector that has taken off thanks to the growth of SaaS is the area of cloud analytics. SaaS grew by leaps and bounds because of its ease of use, and rapid deployment that could be achieved by business users. Cloud analytics aims to provide the same ease of use for business users when providing deep insights into data in an interactive manner.
In all these different sectors, what’s common is the fact that SaaS growth has created an uptick in the volume of data and the technologies that serve to make it easier to understand. During Informatica’s Data Mania event (March 4th, San Francisco) you’ll find several esteemed executives from Salesforce, Amazon, Adobe, Microsoft, Dun & Bradstreet, Qlik, Marketo, and AppDynamics talk about the importance of data in the world of SaaS.
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.
Amazon Redshift, one of the fast-rising stars in the AWS ecosystem has taken the data warehousing world by storm ever since it was introduced almost two years ago. Amazon Redshift operates completely in the cloud, and allows you to provision nodes on-demand. This model allows you to overcome many of the pains associated with traditional data warehousing techniques, such as provisioning extra server hardware, sizing and preparing databases for loading or extensive SQL scripting.
However, when loading data into Redshift, you may find it challenging to do so in a timely manner. To reduce the time taken to load this data, you may have to spend a tremendous amount of time writing SQL optimization queries which takes away the value proposition of using Redshift in the first place.
Informatica Cloud helps you load this data quickly into Redshift in just a few minutes. To start using Informatica Cloud, you’ll need to establish connections from Redshift and your other data source first. Here are a few easy steps to help you get started with establishing connections from a relational database such as MySQL as well as Redshift into Informatica Cloud:
- Login into your Informatica Cloud account, go to Configure -> Connections, click “New”, and select “MySQL” for “Type”
- Select your Secure Agent and fill in the rest of the database details:
- Test your connection and then click ‘OK’ to save and exit
- Now, login to your AWS account and go to Redshift service page
- Go to your cluster configuration page and make a note of the cluster and cluster database properties: Number of Nodes, Endpoint, Port, Database Name, JDBC URL. You also will need:
- The Redshift database user name and password (which is different from your AWS account)
- AWS account Access Key
- AWS account Secret Key
- Exit the AWS console.
- Now, back in your Informatica Cloud account, go to Configure -> Connections and click “New”.
- Select “AWS Redshift (Informatica)” for “Type” and fill in the rest of the details from the information you have from above
- Test the connection and then click ‘OK’ to save and exit
As you can see, establishing connections was extremely easy and can be done in less than 5 minutes. To learn how customers such as UBM used Informatica Cloud to deliver next-generation customer insights with Amazon Redshift, please join us on September 16 for a webinar where we’ll have product experts from Amazon and UBM explaining how your company can benefit from cloud data warehousing for petabyte-scale analytics using Amazon Redshift.
The mainstream use of SaaS applications as part of the cloud strategies in many enterprises continues to rise. Initially led by LOB IT (lines of business, apps IT), SaaS deployments now have central IT (such as Integration Competency Centers) personnel extensively involved. This shift stems from the need to develop strategies around hybrid application deployments – environments that include integrations between cloud and on-premise applications.
The entire breadth of cloud-to-cloud and cloud-to-ground integration scenarios necessitates interacting with the publicly available APIs, cloud services, and internal web services. The end goal is to enable secure, consistent data access on enterprise apps wherein any cloud, or on-premise application is accessible through a tablet or smartphone, in an intuitive, easy-to-use interface.
A key necessity for hybrid application deployments is the concept of “adaptive integration” within any integration platform-as-a-service (iPaaS). Any cloud service integration that claims to have iPaaS capabilities needs to have integration features that connect data, applications, and processes, as well as have governance and API management functionality. The iPaaS must also run on a multi-tenant infrastructure and be available on-premise at times.
You can learn more about adaptive integration, how the iPaaS impacts it, and hybrid application strategies in our recorded webinar, Enabling Hybrid Application Strategies through Cloud Service Integration, featuring Gartner Vice-President and Fellow, Massimo Pezzini, and Informatica Senior Vice-President of Data Integration, Ash Kulkarni. Key topics covered will include:
- How SaaS adoption is driving the need for hybrid integration
- Why the mobilization of the enterprise means a stricter criteria for an iPaaS
- How Everton Football Club in the English Premier League gained major customer insights by using Informatica Cloud
- What “Adaptive Integration” and the Internet of Things have in store for us
As Informatica Cloud product managers, we spend a lot of our time thinking about things like relational databases. Recently, we’ve been considering their limitations, and, specifically, how difficult and expensive it is to provision an on-premise data warehouse to handle the petabytes of fluid data generated by cloud applications and social media. As a result, companies have to often make tradeoffs and decide which data is worth putting into their data warehouse.
Certainly, relational databases have enormous value. They’ve been around for several decades and have served as a bulwark for storing and analyzing structured data. Without them, we wouldn’t be able to extract and store data from on-premise CRM, ERP and HR applications and push it downstream for BI applications to consume.
With the advent of cloud applications and social media however, we are now faced with managing a daily barrage of massive amounts of rapidly changing data, as well as the complexities of analyzing it within the same context as data from on-premise applications. Add to that the stream of data coming from Big Data sources such as Hadoop which then needs to be organized into a structured format so that various correlation analyses can be run by BI applications – and you can begin to understand the enormity of the problem.
Up until now, the only solution has been to throw development resources at legacy on-premise databases, and hope for the best. But given the cost and complexity, this is clearly not a sustainable long-term strategy.
As an alternative, Amazon Redshift, a petabyte-scale data warehouse service in the cloud has the right combination of performance and capabilities to handle the demands of social media and cloud app data, without the additional complexity or expense. Its Massively Parallel Processing (MPP) architecture allows for the lightning fast loading and querying of data. It also features a larger block size, which reduces the number of I/O requests needed to load data, and leads to better performance.
By combining Informatica Cloud with Amazon Redshift’s parallel loading architecture, you can make use of push-down optimization algorithms, which process data transformations in the most optimal source or target database engines. Informatica Cloud also offers native connectivity to cloud and social media apps, such as Salesforce, NetSuite, Workday, LinkedIn, and Twitter, to name a few, which makes it easy to funnel data from these apps into your Amazon Redshift cluster at faster speeds.
If you’re at the Amazon Web Services Summit today in New York City, then you heard our announcement that Informatica Cloud is offering a free 60-day trial for Amazon Redshift with no limitations on the number of rows, jobs, application endpoints, or scheduling. If you’d like to learn more, please visit our Redshift Trial page or go directly to the trial.
With practically every on-premise application having a counterpart in the SaaS world, enterprise IT departments have truly made the leap to a new way of computing that is transforming their organizations. The last mile of cloud transformation lies in the field of integration, and it is for this purpose that Informatica had a dedicated Cloud Day this year at Informatica World 2014.
The day kicked off with an introduction by Ronen Schwartz, VP and GM of Informatica Cloud, to the themes of intelligent data integration, comprehensive cloud data management, and cloud process automation. The point was made that with SaaS applications being customized frequently, and the need for more data insights from these apps, it is important to have a single platform that can excel at both batch and real-time integration. A whole series of exciting panel discussions followed, ranging from mission critical Salesforce.com integration, to cloud data warehouses, to hybrid integration use cases involving Informatica PowerCenter and Informatica Cloud.
In the mission critical Salesforce.com integration panel, we had speakers from Intuit, InsideTrack, and Cloud Sherpas. Intuit talked about how they went live with Informatica Cloud in under four weeks, with only two developers on hand. InsideTrack had an interesting use case, wherein, they were using the force.com platform to build a native app that tracked performance of students and the impact of coaching on them. InsideTrack connected to several databases outside the Salesforce platform to perform sophisticated analytics and bring them into their app through the power of Informatica Cloud. Cloud Sherpas, a premier System Integrator, and close partner of both Salesforce.com and Informatica outlined three customer case studies of how they used Informatica Cloud to solve complex integration challenges. The first was a medical devices company that was trying to receive up-to-the-minute price quotes be integrating Salesforce and SAP, the second was a global pharmaceuticals company that was using Salesforce to capture data about their research subjects and needed to synchronize that information with their databases, and the third was Salesforce.com itself.
The die-hard data geeks came out in full force for the cloud data warehousing panel. Accomplished speakers from Microstrategy, Amazon, and The Weather Channel discussed data warehousing using Amazon Web Services. A first-time attendee to this panel would have assumed that cloud data warehousing simply dealt with running relational databases on virtual machines spun up from EC2, but instead participants were in enthralled to learn that Amazon Redshift was a relational database that ran 100% in the cloud. The Weather Channel uses Amazon Redshift to perform analytics on almost 750 million rows of data. Using Informatica Cloud, they can load this data into Redshift in a mere half hour. Microstrategy talked about their cloud analytics initiatives and how they looked at it holistically from a hybrid standpoint.
On that note, it was time for the panel of hybrid integration practitioners to take the stage, with Qualcomm and Conde Nast discussing their use of PowerCenter and Cloud. Qualcomm emphasized that the value of Informatica Cloud was the easy access to a variety of connectors, and that they were using connectors for Salesforce, NetSuite, several relational databases, and web services. Conde Nast mentioned that it was extremely easy to port mappings between PowerCenter and Cloud due to the common code base between the two.
Salesforce.com is one of the most widely used cloud applications across every industry. Initially, Salesforce gained dominance from mid-market customers due to the agility and ease of deployment that the SaaS approach delivered. A cloud-based CRM system enabled SMB companies to easily automate sales processes that recorded customer interactions during the sales cycle and scale without costly infrastructure to maintain. This resulted in faster growth, thereby showing rapid ROI of a Salesforce deployment in most cases.
The Eye of the Enterprise
When larger enterprises saw the rapid growth that mid-market players had achieved, they realized that Salesforce was a unique technology enabler capable of helping their businesses to also speed time to market and scale more effectively. In most enterpises, the Salesforce deployments were driven by line-of-business units such as Sales and Customer Service, with varying degrees of coordination with central IT groups – in fact, most initial deployments of Salesforce orgs were done fairly autonomously from central IT.
With Great Growth Comes Greater Integration Challenges
When these business units needed to engage with each other to run cross functional tasks, the lack of a single customer view across the siloed Salesforce instances became a problem. Each individual Salesforce org had its own version of the truth and it was impossible to locate where in the sales cycle each customer was in respect to each business unit. As a consequence, cross-selling and upselling became very difficult. In short, the very application that was a key technology enabler for growth was now posing challenges to meet business objectives.
Scaling for Growth with Custom Apps
While many companies use the pre-packaged functionality in Salesforce, ISVs have also begun building custom apps using the Force.com platform due to its extensibility and rapid customization features. By using Salesforce to build native applications from the ground up, they could design innovative user interfaces that expose powerful functionality to end users. However, to truly add value, it was not just the user interface that was important, but also the back-end of the technology stack. This was especially evident when it came to aggregating data from several sources, and surfacing them in the custom Force.com apps.
On April 23rd at 10am PDT, you’ll hear how two CIOs from two different companies tackled the above integration challenges with Salesforce: Rising Star finalist of the 2013 Silicon Valley Business Journal CIO Awards, Eric Johnson of Informatica, and Computerworld’s 2014 Premier 100 IT Leaders, Derald Sue of InsideTrack.
SaaS companies are growing rapidly and becoming the top priority for most CIOs. With such high growth expectations, many SaaS vendors are investing in sales and marketing to acquire new customers even if it means having a negative net profit margin as a result. Moreover, with the pressure to grow rapidly, there is an increased urgency to ensure that the Average Sales Price (ASP) of every transaction increases in order to meet revenue targets.
The nature of the cloud allows these SaaS companies to release new features every few months, which sales reps can then promote to new customers. When new functionalities are not used nor understood, customers often feel that they have overpaid for a SaaS product. In such cases, customers usually downgrade to a lower-priced edition or worse, leave the vendor entirely. To make up for this loss, the sales representatives must work harder to acquire new leads, which results in less attention for existing customers. Preventing customer churn is very important. The Cost to Acquire a Customer (CAC) for upsells is 19% of the CAC to acquire new customer dollars. In comparison, the CAC to renew existing customers is only 15% of the CAC to acquire new customer dollars.
Accurate customer usage data helps determine which features customers use and which are under utilized. Gathering this data can help pinpoint high-value features that are not used, especially for customers that have recently upgraded to a higher edition. The process of collecting this data involves several touch points – from recording clicks within the app to analyzing the open rate of entire modules. This is where embedded cloud integration comes into play.
Embedding integration within a SaaS application allows vendors to gain operational insights into each aspect of how their app is being used. With this data, vendors are able to provide feedback to product management in regards to further improvements. Additionally, embedding integration can alert the customer success management team of potential churn, thereby allowing them to implement preventative measures.
To learn more about how a specialized analytics environment can be set up for SaaS apps, join Informatica and Gainsight on April 9th at 10am PDT for an informational webinar Powering Customer Analytics with Embedded Cloud Integration.
Within most organizations today, it is not a question of if SaaS applications should be deployed, but how quickly. The era of having to justify adoption of SaaS applications is long over, and the focus has shifted towards a deciding which SaaS applications to deploy, in which departments, and in what timeframes. With this view in mind, let us explore the typical journey that most companies take when deciding which SaaS applications to implement first.
Related: Learn more about customer facing processes vs. customer fulfillment processes in the March 25th webinar ‘Accelerate Business Velocity with NetSuite and Salesforce Integration’
Customer Facing Processes
The main impetus behind switching to a SaaS application is because of the agility the cloud brings. Customizations that normally take weeks to get implemented take minutes or days, and can be performed by employees that do not possess an in-depth knowledge of the technical infrastructure of the SaaS system. With that being said, it is customer-facing processes that require application customizations almost immediately because optimizing these processes results in bringing in revenue quickly into the company, thereby enabling CIOs to show rapid ROI of a SaaS application.
It is no wonder that front-office applications such as Salesforce have become one of the largest SaaS vendors out there today. The entire process of converting a lead to a closed opportunity has several steps in between, and may require multiple workflows in parallel. But the journey doesn’t stop there. To keep customers satisfied and retain them, their product needs to be fulfilled, and this is where customer fulfillment processes come into play.
Customer Fulfillment Processes
Once an opportunity has been closed, the process of getting the product to the customer begins. Traditionally, this role has been done by large-scale on-premise ERP vendors, but leading cloud ERP companies such as NetSuite are showing how the complex task of fulfilling orders and realizing revenue can be done faster. Processes such as applying category-specific price and quantity discounts, special tax regulations involving several regions and nations, and fulfillment through multiple delivery options all have several moving parts. Moreover, the task of invoicing the customer, collecting payment, and recording numerous financial transactions is an entire sub-process in of itself and the only way it can be streamlined is through cloud ERP applications.
Optimizing the Entire Lead-to-Cash Process with Cloud Integration
When looking at customer-facing and customer-fulfillment processes together, it is very clear that SaaS apps in both categories need to work hand-in-hand to ensure that an organization’s customers are satisfied, and continue to engage in repeat business. This is why organizations that are starting the rollout of front-office SaaS applications also need to be thinking about rolling out back-office ERP SaaS applications along with a cloud integration solution to tie it all together. In the March 25th webinar, ‘Accelerate Business Velocity with NetSuite and Salesforce Integration’, we’ll talk about a blueprint for integrating both these types of apps together and how the Australian Institute of Management deployed these apps as part of a multi-million dollar IT transformation project.
An explosion in mobile devices and social media usage has been the driving force behind large brands using big data solutions for deep, insightful analytics. In fact, a recent mobile consumer survey found that 71% of people used their mobile devices to access social media.
With social media becoming a major avenue for advertising, and mobile devices being the medium of access, there are numerous data points that global brands can cross-reference to get a more complete picture of their consumer, and their buying propensities. Analyzing these multitudes of data points is the reason behind the rise of big data solutions such as Hadoop.
However, Hadoop itself is only one Big Data framework, and consists of several different flavors. Facebook, which called itself the owner of the world’s largest Hadoop cluster, at 100 petabytes, outgrew its capabilities on Hadoop and is looking into a technology which would allow it to abstract its Hadoop workloads across several geographically dispersed datacenters.
When it comes to analytics projects that require intensive data warehousing, there is no one-size fits all answer for Big Data as the use cases can be extremely varied, ranging from short-term to long-term. Deploying Hadoop clusters requires specialized skills and proper capacity planning. In contrast, Big Data solutions in the cloud such as Amazon RedShift allow users to provision database nodes on demand and in a matter of minutes, without the need to take into account large outlays of infrastructure such as servers, and datacenter space. As a result, cloud-based Big Data can be a viable alternative for short-term analytics projects as well as fulfilling sandbox requirements to test out larger Big Data integration projects. Cloud-based Big Data may also make sense in situations where only a subset of the data is required for analysis as opposed to the entire dataset.
With cloud integration, much of the complexity of connecting to data sources and targets is abstracted away. Consequently, when a cloud-based Big Data deployment is combined with a cloud integration solution, it can result in even more time and cost savings and get the projects off the ground much faster.
We’ll be discussing several use cases around cloud-based Big Data in our webinar on August 22nd, Big Data in the Cloud with Informatica Cloud and Amazon Redshift, with special guests from Amazon on the event.