Business · Data

Understanding the value of data integration

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

Microsoft empowers the developer at Connect

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This week at Microsoft Connect in New York City, Microsoft announced a number of products geared toward bringing intelligence and the computing edge closer together. The tools continue Microsoft’s support of a varied and growing ecosystem of evolving solutions. At the same time, Microsoft demonstrated their insatiable drive to woo the developer with a number of tools geared toward modern development and advanced technology.

EMBRACING THE ECOSYSTEM DIVERSITY

Microsoft has tried hard in the past several years to shed their persona of Microsoft-centricity of a .NET Windows world. Similar to their very vocal support for inclusion and diversity in culture, Microsoft brings that same perspective to the tools, solutions and ecosystems they support. The reality is that the world is diverse and it is this very diversity that makes us stronger. Technology is no different.

At the Connect conference, similar to their recent Build & Ignite conferences, .NET almost became a footnote as much of the discussion was around other tools and frameworks. In many ways, PHP, Java, Node and Python appeared to get mentioned more than .NET. Does this mean that .NET is being deprecated in favor of newer solutions? No. But it does show that Microsoft is moving beyond just words in their drive toward inclusivity.

EXPANDING THE DEVELOPER TOOLS

At Connect, Microsoft announced a number of tools aimed squarely at supporting the modern developer. This is not the developer of years past. Today’s developer works in a variety of tools, with different methods and potentially in separate locations. Yet, they need the ability to collaborate in a meaningful way. Enter Visual Studio Live Share. What makes VS Live Share interesting is how it supports collaboration between developers in a more seamless way without the cumbersome screen sharing approach previously used. The level of sophistication that VS Live Share brings is impressive in that it allows each developer to walk through code in their own way while they debug and collaborate. While VS Live Share is only in preview, other recently-announced tools are already seeing significant adoption in a short period of time that ranges in the millions of downloads.

In the same vein of collaboration and integration, DevOps is of keen interest to most enterprise IT shops. Microsoft showed how Visual Studio Team Services embraces DevOps in a holistic way. While the demonstration was impressive, the question of scalability often comes into the picture for large, integrated teams. It was mentioned that VS Team Services is currently used by the Microsoft Windows development team and their whopping 25,000 developers.

Add to scale the ability to build ‘safe code’ pipelines with automation that creates triggers to evaluate code in-process and one can quickly see how Microsoft is taking the modern, sophisticated development process to heart.

POWERING DATA AND AI IN THE CLOUD

In addition to developer tools, time was spent talking about Azure, data and Databricks. I had the chance to sit down with Databricks CEO Ari Ghodsi to talk about how Azure Databricks is bringing the myriad of data sources together for the enterprise. The combination of Databricks on Azure provides the scale and ecosystem that highlights the power of Databricks to integrate the varied data sources that every enterprise is trying to tap into.

MIND THE DEVELOPER GAP

Developing applications that leverage analytics and AI is incredibly important, but not a trivial task. It often requires a combination of skills and experience to fully appreciate the value that comes from AI. Unfortunately, developers often do not have the data science skills nor business context needed in today’s world. I spoke with Microsoft’s Corey Sanders after his keynote about how Microsoft is bridging the gap for the developer. Both Sanders & Ghodsi agree that the gap is an issue. However, through the use of increasingly sophisticated tools such as Databricks and Visual Studio, Sanders & Ghodsi believe Microsoft is making a serious attempt at bridging this gap.

It is clear that Microsoft is getting back to its roots and considering the importance of the developer in an enterprise’s digital transformation journey. While there are still many gaps to fill, it is interesting to see how Microsoft is approaching the evolving landscape and complexity that is the enterprise reality.

Business · CIO · Cloud · Data

How Important are Ecosystems? Ecosystems are Everything

The IT industry is in a state of significant flux. Paradigms are changing and so are the underlying technologies. Along with these changes come the way we think about solutions. Over time, IT organizations have amassed a phenomenal number of solutions, vendors, complex configurations and experience. Continuing to support that ever-expanding model is starting to show cracks. Trying to sustain this approach is just not possible…nor should it be. It is time for a change. Consolidation, integration, efficiency and value creation are the current focal points. Those shifts create a significant shift in how we function as IT organizations and providers.

Changes in Buying Habits

In order to truly understand the value of an ecosystem, one first needs to understand the change in buying habits. IT organizations are making a significant shift from buying point solutions to buying ecosystems. In some ways, this is nothing new. IT organizations have bought into the solutions from major providers for decades. The change is in the composition of the ecosystem. Instead of buying into an ecosystem from a single provider, buyers are looking for comprehensive ecosystems that span multiple providers. This lowers the risk for the buyer and creates a broader offering while providing an integrated solution.

Creating the Cloud Supply Chain

Cloud Computing is a great use-case of the importance of building a supply chain within the ecosystem. Think about it. Applications, services and solutions that IT organization provides to users are not single-purpose, non-integrated solutions. At least they shouldn’t be. Good applications and services are integrated with other offerings. When buyers choose a component, that component needs to connect to another component. In addition, alternatives are needed, as one solution does not fit all. In many ways, this is no different from a traditional manufacturing supply chain. The change is to apply those fundamentals to the cloud ecosystem.

Integration

In concert with the supply chain, each component needs solid integration with the next. Today, many point solutions require the buyer to figure out how to integrate solutions. This often becomes a barrier to adoption and introduces risk into the process. One could go crazy coming up with the permutations of different solutions that connect. However, if each solution considered the top 3-4 commonly connected components, the integration requirements become more manageable. And they are left to the folks that understand the solutions best…the providers.

Cloud Verticals

As cloud-based ecosystems start to mature, the natural progression is to develop cloud verticals. Essentially, creating ecosystems with components for a specific vertical or industry. In the healthcare vertical, an ecosystem might include a choice of EHR solutions, billing systems, claims systems and patient portal. For SMB or Mid-Tier businesses, it might be an accounting system, email, file storage and website. Remember that the ecosystem is not just a brokerage of selling the solutions as a package. It is a comprehensive solution that is already integrated.

Bottom Line: Buyers are moving to buying ecosystems, especially with cloud services. The value of your solution comes from the value of your ecosystem.