Tag: machine learning

Business · Cloud · Data

Shifting the thinking of enterprise applications

Tim Crawford2 Comments

Enterprise applications are not new and have been around for decades. Since their start, enterprise applications have increased in their level of sophistication and business automation. However, this sophistication comes with a significant degree of complexity too.

Historically, enterprises were in the position where they needed to build everything themselves. Much of this stemmed from the fact there were limited options to consider. Fast forward to today and there are a myriad of options of how an enterprise can consume an enterprise application.

However, getting from here to there is not trivial. Practically every enterprise application has a strong degree of complexity that is directly tied to the intricacies of their specific business operations. For decades, enterprises have taken the approach of customizing the application to match their existing business processes. Due to the degree of customization, every enterprise Information Technology (IT) organization essentially created their own enterprise application snowflake.

CHANGING THE ENTERPRISE APPLICATION PARADIGM

One of the challenges for enterprise applications in the cost to upgrade. All of the unique customizations significantly increase the cost and complexity to upgrade the system. The customizations, related programming, configuration and testing involved turn each upgrade into the equivalent of a new implementation.

For many enterprises, it is common practice to skip versions rather than maintain currency due to the cost and disruption associated with the complexity to upgrade. This also means that many enterprises delay their ability to leverage new functionality.

New opportunities from cloud computing and Artificial Intelligence (AI) present unique opportunities to enterprise applications. With cloud-based enterprise applications, no longer is the enterprise required to install, manage and operate the underlying enterprise application. As applications increase in their level of complexity, this takes an increasingly huge burden off the shoulders of the IT organization.

AI presents a different type of opportunity. Enterprises are increasingly their reliance on data to gain greater insights. The volume and types of data are adding increased pressure on the traditional methods to analyze data. AI presents a unique opportunity to automate the process and gain insights not previously possible. However, the more data available to the AI algorithm, the more supportive it can be. And that is where cloud comes in to provide additional resources in a meaningful way when needed without the need to build a fortress internally.

TRADITIONAL VERSUS TRANSFORMATIONAL

Of late, enterprise IT organizations are shifting their focus from a traditionalIT organization to that of a transformationalIT organization. That is to say that their focus is shifting from technology-centricto business-centric. As part of this shift, IT organizations are looking for ways to streamline their technical operations and focus more on data and insights.

The shift to transformational IT organizations is having an impact on the most sacred applications within the IT portfolio including the enterprise applications.

MATURING THE THINKING ABOUT ENTERPRISE APPLICATIONS

More mature enterprises are starting to shift their thinking about enterprise applications. This is due to a number of factors including 1) IT organizations are shifting their focus on business-centric outcomes, 2) Mature alternatives exist for even the largest of implementations 3) The pressure to implement advanced functions is increasing and 4) The speed in which IT organizations must respond with changes is increasing.

Each of these pose a significant challenge to the traditional approach of maintaining enterprise applications. The only real solution is to change the thinking around enterprise applications to avoid proliferating snowflakes.

 

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Business · Data

Understanding the value of data integration

Tim CrawfordLeave a comment

To understand the value of data integration, one has to first understand the changing data landscape. In the past few years, more data has been created than existed in all of time prior to that. In 2014, I penned a post asking ‘Are enterprises prepared for the data tsunami’? When it comes to data, enterprises of all sizes and maturity face two core issues: 1) How to effectively manage the sheer volume of data in a meaningful way and 2) How to extract insights from the data. Unfortunately, the traditional ways to manage data start to break down when considering these new challenges.

DIVERSE DATA SETS

In the above-mentioned post, there was reference to an IDC report suggesting that by 2020, the total amount of data will equate to 40,000 exabytes or 40 trillion gigabytes. That is more than 5,200 gigabytes for every man, woman and child in 2020.

However, unlike data in the past, this new data will come from an increasingly varied list of sources. Some of the data will be structured. Other data will be unstructured. And then there is meta data that is derived through analysis of these varied data sets. All of which needs to be leveraged by the transformational enterprise.

In the past, one might have pooled all of this data into a classic data warehouse. Unfortunately, many of the new data types do not fit nicely into this approach. Then came the data lake as a solution to simply pool all of this data. Unfortunately, this approach is also met with challenges as many enterprises are seeing their data lakes turn into data swamps.

Even beyond data generated internally enterprises are increasing their reliance on externally sourced data. Since this data is not created by the enterprise, there are limits on how the data is leveraged. In addition, simply bringing all of this data into the enterprise is not that simple. Nor is it feasible.

Beyond the concept of different data sets, these new data sets create ‘data gravity’ as they grow in size. Essentially, creating a stronger bond between the data set and the application that leverages it. As the size of the data set grows, so does its ‘gravity’ which prevents movement. All of these reasons create significant friction to considering any movement of data.

VALUE OF INTEGRATING DATA

The solution rests with data integration. Essentially, leave data where it resides and leverage integration methods to the various data sets in order to create insights. There are actually two components when considering how to integrate data.

There is a physical need for data integration and one that is more logical in nature. The physical component is how to physically connect the different data sources together. This is easier said than done. It was already challenging when we managed all of the data within the enterprise. Today, the data resides in the hands of many other players and approaches. This can add complexity to the integration efforts. Modern data integration methods rely on Application Programming Interfaces (APIs) to create these integration points. In addition, there are security ramifications to consider too.

The logical integration of data often centers around the customer. One of the core objectives for enterprises today is customer engagement. Enterprises are finding ways to learn more about their customer in an effort to build a more holistic profile that ultimately leads to a stronger relationship. Not all of that data is sourced internally. This really is a case of 1+1=3 where even smaller insights can lead to a larger impact when combined.

THE INTERSECTION OF DATA INTEGRATION AND ADVANCED FUNCTIONS

Data integration is a deep and complicated subject that is evolving quickly. Newer advancements in the Artificial Intelligence (AI) space are leading enterprises to gain greater insights that even they didn’t think about. Imagine a situation where you thought you knew your customer, but the system suggested other aspects that weren’t considered. AI has the opportunity to significantly augment the human capability to create more accurate insights and faster.

Beyond AI, other newer functions such as Machine Learning (ML) and Internet of Things (IoT) present new sources of data to further enhance insights. It should be noted that nether ML nor IoT are able to function in a meaningful way without leveraging data integration.

DATA INTEGRATION LEADS TO SPEED AND INSIGHTS…AND CHALLENGES

Enterprises that leverage AI and ML to augment their efforts find increased value from both the insights and the speed in which they respond. In today’s world where speed and accuracy are becoming a strong differentiation for competitors, leveraging as much data as possible is key. In order to leverage the sheer amount of data, enterprises must leverage data integration to remain competitive.

At the same time, enterprises are facing challenges from new regulations such as the General Data Protection Regulation (GDPR). There are many facets and complexities to GDPR that will only further the complexities for data integration and management.

While enterprises may have leveraged custom approaches to solve the data integration problem in the past, today’s complexities demand a different approach. The combination of these challenges push enterprises to leverage advanced tools to assist in the integration of data to gain greater insights.

 

This post sponsored by:

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https://www.sap.com/intelligentdata

Business · Cloud · Data

How cloud is changing the business and IT landscape

Tim CrawfordLeave a comment

 

Enterprises around the globe are facing disruption from a number of different directions. To combat this disruption, they increasingly turn to cloud computing.

Cloud computing is the single biggest opportunity for organizations to dramatically change how their business operates through changes in their Information Technology (IT) landscape. Organizations are evaluating ways to leverage cloud-based solutions in differentiated ways. As these organizations evaluate how best to leverage cloud, there are a number of factors to consider when moving into a cloud-based world.

SHIFTING HOW WE THINK ABOUT ORGANIZATIONS

The move for enterprises leveraging cloud-based technology causes more than just a shift in technology. It also causes a shift in how we think about strategy, organization and culture. In the past, enterprises were required to build their strategy, organization and support around the entire technology platform. There were few to no other reasonable options.

In the cloud-based era, those aspects change. Today, there are mature, viable solutions that allow the enterprise to leverage alternatives. By shifting functions that are important but not strategic nor differentiated, it allows organizations to shift their focus as well.

By making this shift, organizations are able to up-level conversations and focus on business outcomes rather than technology features. These changes open the door to other shifts as well.

CHANGING THE WAY WE WORK

Two of those shifts directly impact the advantage to a business and their customers. The first shift is leverage. Cloud computing provides leverage in ways not previously feasible. IT organizations now have access to a bevy of solutions and virtually unlimited resources. Prior to cloud computing, organizations were limited in their ability to quickly scale resources and leverage new technology. For many, cost constraints were a significant limitation to potential growth.

Beyond technology, cloud provides the organization with the ability to leverage the expertise of others. As mentioned, previous methods required IT organizations to be an expert across a myriad of strategic and non-strategic areas. With cloud, organizations can focus on those aspects strategic and differentiated for their business and customers. This shifts the organization and culture to focus more directly on solutions that provide business advantage.

The second shift is speed. Unlike past options that may take weeks or months for the availability of applications and resources, cloud shortens the time to a matter of minutes. As businesses are looking for ways to respond quickly to ever-changing customer requirements, this rapid flexibility provides the organization with the ability to respond in a timely fashion.

OPENING UP NEW OPPORTUNITES

Aside from speed, cloud opens up a whole new world of opportunity for organizations. Historically, there was a minimum cost of entry for many of the more advanced systems. Unfortunately, these costs were far outside the realm of possibility for Small and Medium Businesses (SMB). With cloud, SMB organizations now have access to the same solutions as the largest of enterprises. Essentially, this levels the playing field by lowering the barriers to entry of these advanced systems.

As organizations shift toward a greater focus on customers through quicker and more accurate business decisions, so does their reliance on data. At the same time, organizations are facing an explosion of data. Traditional reporting and analytics are collapsing under the weight of this new influx of data.

To combat the data deluge, organizations are increasing their reliance on Artificial Intelligence (AI) and Machine Learning (ML) to automate the insights gleaned from the data. While AI & ML require large quantities of data, traditional solutions are simply unable to provide the resources that AI & ML algorithms require. Again, cloud computing opens the door to organizations, large and small, to leverage these advanced functions.

BRINGING IT TOGETHER

The combination of cloud-based resources with advanced functions provide organizations with new opportunities to glean greater insights much quicker than previously possible. Cloud’s leverage provides organizations the ability to shift the IT landscape to focus on business outcomes and strategic initiatives rather than deep technical expertise.

In summary, cloud computing presents not only an alternative option for technology consumption, but a required pillar for tomorrow’s business.

 

This post is sponsored by:

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https://www.sap.com/intelligentdata

Cloud

Four expectations for AWS re:Invent

Tim CrawfordLeave a comment

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This week brings Amazon Web Services’ (AWS) annual re:Invent conference where thousands will descend upon Las Vegas to learn about cloud and the latest in AWS innovations. Having attended the conference for several years now, there are a number of trends that are common at an AWS event. One of those is the sheer number of products that AWS announces. Aside from that, there are a number of specific things I am looking for at this week’s re:Invent conference.

ENTERPRISE ENGAGEMENT

AWS has done a stellar job of attracting the startup and web-scale markets to their platform. The enterprise market, however, has proven to be an elusive customer except for a (relatively) few case examples. This week, I am looking to see how things have changed for enterprise adoption of AWS. Has AWS found the secret sauce to engage the enterprise in earnest?

PORTFOLIO MANAGEMENT

Several years back, AWS made a big point of not being one of “those” companies with a very large portfolio of products and services. Yet, several years later, AWS has indeed become a behemoth with a portfolio of products and services a mile long. This is a great thing for customers, but can have a few downsides too. Customers, especially enterprise customers, tend to make decisions that last longer than the startup & web-scale customers. Therefore, service deprecation is a real concern with companies that a) do not have a major enterprise focus and b) have a very large portfolio. Unfortunately, this is where AWS is today. Similarly, to date, AWS has not done much in the way of portfolio pruning.

HYBRID CLOUD SUPPORT

For the enterprise, hybrid is their reality. In the past, AWS has taken the position that hybrid means a way to onboard customers into AWS Public Cloud. Hybrid, a combination of on-premises and cloud-based resources can be a means to onboard customers into public cloud. The question is: How is AWS evolving their thinking of hybrid cloud? In addition, how has their thinking evolved to encompass hybrid cloud from the perspective of the enterprise?

DEMOCRATIZATION OF AI & ML

Several of AWS’ competitors have done a great job of democratizing artificial intelligence (AI) and machine learning (ML) tools in a means to make them more approachable. AWS was one of the first out of the gate with a strong showing of AI & ML tools a few years back. The question is: How have they evolved in the past year to make the tools more approachable for the common developer?

BONUS ROUND

As a bonus, it would be interesting if AWS announced the location of their 2nd headquarters. Will they announce it at re:Invent versus a financial analyst call? We shall see.

In summary, AWS never fails to put on a great conference with a good showing. This year should not disappoint.

Business · CIO · Cloud

IBM Interconnect expectations, a CIOs perspective

Tim CrawfordLeave a comment

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This week is IBM’s annual cloud conference in Las Vegas. Quite a bit has changed in the past year for IBM and at this year’s IBM Interconnect there are a few things I’m looking for. Each of them centers in the mainstream of enterprise demand. Here’s the quick rundown:

IBM CLOUD CURRENT STATE AND DIRECTION

Over the past several years, IBM made strategic acquisitions that feed directly into IBM’s core cloud strategy. Those include Softlayer and Bluebox Cloud. Since last year’s Interconnect conference, I’m looking to hear how things have progressed and how it impacts their direction. Both are key attributes to enterprise engagement.

UNDERSTANDING THE IBM CUSTOMER

IBM is well known for catering to their existing customer base. As enterprises evolve, I’m looking for indications on how non-IBM enterprise customers are choosing to engage IBM. Is most of the demand still coming from existing IBM customers? Or have others started to gravitate toward IBM…and why?

In addition, how has the recent partnership announcement with Salesforce changed this engagement? Granted, the ink is still wet on the agreement, but there may be a few tidbits to glean here.

PORTFOLIO HALO EFFECTS

IBM’s Watson provides an interesting opportunity for enterprises looking to engage analytics, machine learning (ML) and artificial intelligence (AI). Watson, along with the strides IBM has made with Internet of Things (IoT) provides some interesting opportunities for both existing and prospective IBM customers. I’m looking to see if these are creating a halo effect into IBM’s cloud business…and if so, how and where.

LEADERSHIP CHANGES

Finally, IBM is changing up the leadership team. Longtime IBM’er Robert LeBlanc has departed from leading the IBM Cloud division and changes are afoot in marketing. How will these changes impact how IBM approaches cloud and how IBM is perceived in the broader enterprise market?

 

Overall, IBM is clamoring to be a leader in the enterprise cloud space, but faces some stiff competition. Cloud has been a key element in IBM’s enterprise portfolio for some time. This week should provide greater insights on their current state and path moving forward.

Business · Cloud · Data

Amazon drives cloud innovation toward the enterprise

Tim CrawfordLeave a comment

 

Amazon continues to drive forward with innovation at a blistering pace. At their annual re:Invent confab, Amazon announced dozens of products to an audience of over 30,000 attendees. There are plenty of newsworthy posts outlining the specific announcements including Amazon’s own re:Invent website. However, there are several announcements that specifically address the growing enterprise demand for cloud computing resources.

INNOVATION AT A RAPID SCALE

One thing that stuck out at the conference was the rate in which Amazon is innovating. Amazon is innovating so fast it is often hard to keep up with the changes. On one hand, it helps Amazon check the boxes when compared against other products. On the other hand, new products like Amazon Rekognition, Polly and Lex demonstrate the level of sophistication that Amazon can bring to market beyond simple infrastructure services. By leveraging their internal expertise in AI and Machine Learning, Amazon’s challenge is one of productizing the solutions.

The sheer number of new, innovative solutions is remarkable but makes it hard to keep track of the best solutions to use for different situations. In addition, it creates a bulging portfolio of services like that of its traditional corporate software competitors.

As an enterprise uses more of Amazon’s products, the fear of lock-in grows. Should this be a concern to either Amazon or potential enterprise customers? Read my post: Is the concept of enterprise lock in a red herring? Lock in is a reality across cloud providers today, not just Amazon. Building solutions for one platform does not provide for easy migration to competing solutions. Innovation is a good thing, but does come at a cost.

DRIVING TOWARD THE EDGE

There are two issues that challenge enterprises evaluating the potential of cloud computing. One challenge is the delivery mechanism. Not all applications are well suited for a centralized cloud-based delivery approach. There are use cases in just about every industry where computing is best suited at the edge. The concept of hybrid cloud computing is one way to address it. At re:Invent, Amazon announced Greengrass which moves the computing capability of Amazon’s Lambda function to a device. At the extreme, Greengrass enables the ability to embed cloud computing functions on a chip.

Moving cloud functionality to the edge is one issue. A second perspective is that it signals Amazon’s acknowledgement that not all roads end with public cloud. The reality is that most industries have use cases where centralized cloud computing is simply not an option. One example, of many, is processing at a remote location. Backhauling data to the cloud for processing is not a viable option. In addition, Internet of Things (IoT) is presenting opportunities and challenges for cloud. The combination of Greengrass and, also announced, Snowball Edge extend Amazon’s reach to the edge of the computing landscape.

AS THE SNOWBALL ROLLS DOWNHILL…

As a snowball rolls downhill, it grows in size. Last year, Amazon announced the data storage onboarding appliance, Snowball. Since last year’s re:Invent, Amazon found customers were using Snowball in numbers exceeding expectations. In addition to the sheer number of Snowball devices, customers are moving larger quantities of data onto Amazon’s cloud. Keep in mind it is still faster to move large quantities of data via truck than over the wire. To address this increase in demand, Amazon drove an 18-wheeled semi-truck and trailer on stage to announce Amazon Snowmobile. While everyone thought it was a gimmick, it is quite real. Essentially, Snowmobile is a semi-trailer that houses a massive storage-focused data center. From an enterprise perspective, this addresses one of the core challenges to moving applications to cloud: how to move the data…and lots of it.

IS AMAZON READY FOR ENTERPRISE?

With the announcements made to date, is Amazon truly ready for enterprise demand? Amazon is the clear leader for public cloud services today. They squarely captured the webscale and startup markets. However, a much larger market is still relatively untapped: Enterprises. Unlike the webscale and startup markets, the enterprise market is both exponentially larger and incredibly more complex. Many of these issues are addressed in Eight ways enterprises struggle with public cloud. For any cloud provider, understanding the enterprise is the first of several steps. A second step is in providing products and services that help enterprises with the onboarding process. As an analogy: Building a beautiful highway is one thing. When you ask drivers to build their own onramps, it creates a significant hurdle to adoption. This is precisely the issue for enterprises when it comes to public cloud. Getting from here to there is not a trivial step.

amazon-enterprise-cloud-gap

To counter the enterprise challenges, Amazon is taking steps in the direction of the enterprise. First is the fundamental design of their data centers and network. Amazon understands that enterprises are looking for data center redundancy. One way they address this is by maintaining multiple data centers in each location. After learning about the thoughts and reasons behind some of their strategic decisions, it’s clear there is quite a bit of deep thinking that goes into decisions. That will bode well for enterprises. Second, Amazon announced their partnership with VMware. I addressed my thoughts on the partnership here: VMware and Amazon AWS Partnership: An Enterprise Perspective. A third step is Amazon’s AWS Migration Acceleration Program. This program is led by a former CIO and directly targets enterprises looking to adopt Amazon’s services. In addition to their internal migration organization, Amazon is building out their partner program to increase the number of partners helping enterprises migrate their applications to Amazon.

ALL ROADS DO NOT LEAD TO PUBLIC CLOUD

Even with all the work Amazon is doing to woo enterprise customers, significant challenges exist. Many assume that all roads lead to public cloud. This statement overstates the reality of how companies need to consume computing resources. There are several paths and outcomes supporting the reality of enterprise computing environments.

How Amazon addresses those concerns will directly impact their success in the enterprise market. Amazon is closing the gap, but so are competitors like Microsoft and others.

Business · CIO · Cloud · IoT

Three things to look for at Amazon’s upcoming AWS re:Invent conference

Tim CrawfordLeave a comment

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As folks in the US prepare for the Thanksgiving holiday, those of us in technology are looking to Amazon’s annual cloud confab AWS re:Invent the week after Thanksgiving in Las Vegas. In preparation for the sold-out conference, there are a few things to look for at the conference.

ENTERPRISE ENGAGEMENT

Amazon has done a good job of attracting the Webscale and Startup markets. One could go so far as to say that Amazon has cornered these markets. For these folks, the options are wide open to address their specific and scaling requirements. The requirements for enterprises, however, are vastly different from their webscale and startup counterparts.

Look for indications that Amazon is starting to learn how to engage enterprises and is moving in that direction. The method, language and solutions vary greatly when considering a prospective customer that has an existing footprint over those that are looking to build their first.

INTELLIGENCE: AI & MACHINE LEARNING

Amazon already has a Machine Learning solution in their portfolio today. Look for further expansion beyond just tools and into the realm of intelligence. Amazon has done a great job of create a bevy of infrastructure tools. However, moving into the intelligence space is both necessary and the logical next step in maturing Amazon’s position in this market. Also, look for Amazon’s response to the growing interest in AI solutions. In addition, the combination of AI & Machine Learning is paramount to more mature IoT solutions.

MOVING UP THE STACK

To date, most of Amazon’s portfolio targets the infrastructure end of the stack. There are a few solutions that move up the stack, but not many. Even so, Amazon has done a stellar job of their existing efforts. If, however, Amazon is intending to capture more of the enterprise market and move beyond being simply a tool provider, it needs to move up the stack into the application realm. To date, it is not clear if Amazon has both the capability and strong interest to do so.

Across the board, Amazon’s competition may not have the depth in IaaS cloud that Amazon has today. Nor do they have the ecosystem that Amazon has worked hard to build over the past 10 years. However, what they lack in IaaS depth is countered by their breadth up and down the stack. And while they may lack the breadth of features in the IaaS space compared with AWS, each are quickly catching up and are posting impressive growth rates.

Next week should provide another exciting event for Amazon and those working in the Cloud space. Whether coming from the startup, webscale or enterprise space, all eyes are on Amazon and their next move.