What Is Data Virtualization

Data has undergone a huge shift from being an unimportant asset to being the most valuable asset a company holds. However, just holding the data doesn’t bring many benefits to your organization. To reap the benefits of the data your company collects, data analysis helps you to find valuable insights for the data you hold.

Data lays at the core of many important business decisions. Many companies prefer a data-driven decision-making policy because it greatly reduces guessing and helps the company to shift toward a more accurate form of decision-making. This greatly benefits the company as you have more trust in the choices you make and you can reduce the number of “incorrect” decisions.

For example, say a product company wants to know if users like the new feature they’ve released. They want to decide if they need to make further improvements to the feature or not. To make a more informed decision, the product company collects user satisfaction scores about the new feature. The company can then use the average user satisfaction score to make this decision. Data virtualization helps you to quickly aggregate data from this survey, as well as other important data that influences the decision, in a single, centralized view. This allows your business to make more informed decisions quicker.

This article introduces you to the concept of data virtualization and how it can help your company to make better decisions. Before we start, what are the common problems companies experience with data?

Common Data Problems for Organizations

Here’s a list of data challenges companies commonly experience:

  • It’s hard to understand the data you’ve collected.
  • Different sources of data use different formats, which makes it harder to retrieve insights.
  • Your organization experiences data lag, which means that data isn’t directly available.
  • Your organization isn’t ready to handle and process data. This could be due to, for example, missing data infrastructure and tools.

Now that you’ve read the above data problems, make sure your organization is ready to handle and process data. So what is data virtualization?

What Is Data Virtualization?

Data virtualization is a form of data management that aggregates different data sources. For example, a data virtualization tool might pull data from multiple databases or applications. However, it’s important to understand that it doesn’t copy or move any of the data. You can have multiple data silos.

Data virtualization is capable of creating a single, virtual layer that spans all of those different data sources. This means your organization can access data much faster since there’s no need to move or copy data. Furthermore, this is a major benefit as you can access data in real time. Virtualization improves the agility of the system, and companies can run analytics faster, gaining insights quicker. For many companies, being able to retrieve insights faster is a great competitive advantage!

As mentioned, data virtualization doesn’t copy or move any data. It only stores particular meta information about the different locations of the data that you want to integrate into your data virtualization tool.

What Is the Importance of Data Virtualization?

First of all, data virtualization acts as the pinnacle of data integration. It allows an organization to integrate many different data sources into a single data model. This means companies can manage all of their data from a single, centralized interface.

Moreover, data virtualization is a great tool for collecting, searching, and analyzing data from different sources. Furthermore, as there’s no data copying involved, it’s also a more secure way of managing your data since you don’t have to transfer the data.

In other words, data virtualization helps companies to become more agile and use their data faster, creating a competitive advantage as you receive analytics and insights more quickly.

What Are the Capabilities of Data Virtualization?

This section describes the capabilities of data virtualization and why they matter for your business.

  1. Agility
    A data virtualization tool allows you to represent data in different ways, format data, discover new relationships between data, or create advanced views that provide you with new insights. The options are endless. Agility is the most important capability of data virtualization as it decreases the time to a solution.
  2. High performance
    A data virtualization tool doesn’t copy or move any data. This contributes to its high-performance nature. Less data replication allows for faster data performance.
  3. Caching
    Caching frequently used data helps you to further improve the performance of your data virtualization tool. Whenever you query for data or a specific data view, part of the data is already cached for you. This puts fewer constraints on your network and improves the availability of your data.
  4. Searchability
    A data virtualization tool allows you to create data views that provide you with actionable insights. Furthermore, data virtualization provides you with a single, centralized interface to search your data.

Next, let’s explore the benefits of data virtualization for your organization.

What Are the Benefits of Data Virtualization?

Here are 10 important benefits of employing a data virtualization tool for your organization.

  1. Helps with hiding the data complexity from the different underlying data sources, data formats, and data structures.
  2. Avoids replication of data to improve performance.
  3. Gives real-time data access and insights.
  4. Provides higher data security as no data is replicated or transferred.
  5. Reduces costs since no investments are needed in additional storage solutions.
  6. Allows for faster business decisions based on data insights.
  7. Reduces the need for development resources to integrate all different data sources.
  8. Allows for data governance to be applied efficiently. For example, data rules can be applied with a single operation to all different data sources.
  9. Improves data quality.
  10. Increases productivity as you can quickly integrate new data sources with your current data virtualization tool.

Now that we have a better understanding of the benefits of data virtualization, it’s time to get serious. The next section explains how you can implement data virtualization in your organization.

How to Get Started With Data Virtualization

Do you want to get started with data virtualization for your organization? The most important tip is to start small. Assign a dedicated team who spends time on integrating one or a couple of data sources. Start with data sources that are most valuable for your organization. This way, you’ll see the benefits of data virtualization quickly.

Next, when your team has completed some simple data integrations, it’s time to scale up your operations and use the tool for most of your data sources. You can think about more complex data models, integrate complex data sources, or use data sources with mixed data types.

Furthermore, you can start to experiment with caching to see where it can be applied effectively to gain the most performance benefits. Remember to apply caching to frequently used data or data models.

As a general rule of thumb, prioritize high-value data sources to reap the most benefits.

Conclusion

One final note: data virtualization isn’t the same as data visualization. The two terms are often used interchangeably, but they have very different meanings. Data virtualization isn’t focused on visualizing data. The main goal of data virtualization is to reduce the effort of integrating multiple data sources and providing your organization with a single, centralized interface to view and analyze data.

In the end, the real business value of data virtualization lays in the agility and faster access to data insights. For many organizations active in the industry of big data or predictive analytics, it’s a real competitive advantage to access insights faster than your competitors. This allows you to make profitable decisions faster than the competition.

If you want to learn more, the following YouTube video by DataAcademy further explains the concept of data virtualization in easy-to-understand terms.

Author

This post was written by Michiel Mulders. Michiel is a passionate blockchain developer who loves writing technical content. Besides that, he loves learning about marketing, UX psychology, and entrepreneurship. When he’s not writing, he’s probably enjoying a Belgian beer!

Comparing Configuration and Asset Management

When you’re running an IT organization, it’s not just the business that you have to take care of. One part of running a business is building, creating, and providing what your customers need. The other part is management. Out of all the things you have to manage, configurations and assets are two of the most important.

Although people often think of configuration management and asset management as the same thing, but they are different. People also sometimes confuse these terms with each other. So, in this post, I’ll explain what configuration management and asset management are and how they’re different. Let’s start by understanding each of these terms.

What Is Configuration Management?

Configuration management is the management of configuration items. So, what are configuration items?

Configuration Items

Any organization provides certain services. These services might be the ones being provided to customers or to internal users. Either way, creating and providing these services requires some components. So, any component that needs to be managed to deliver services is called a “configuration item.”

Too confusing? No worries—I’ll explain with an example. Consider that you’re providing a service that tracks an organization’s user data. In this case, you can consider the software to be the component that needs to be managed. It’s important that you manage this software to make sure your service works fine. This means that your software is a configuration item. Another way of defining a configuration item is that it’s a component that’s subject to change to make the service delivery better.

What Information Is to Be Managed?

When you manage the attributes of such configuration items, that’s configuration management. So, what kind of information do you have to manage? You have to manage attributes such as ownership, versioning, licensing, and types. Let’s consider an example in which you’re using software for internal tasks.

Now you’ve identified that the software that provides service is your configuration item. The next step is to manage information related to that software. The software developer will have released different versions of the software with updates and new features. You obviously look out for better versions of the software or the version that best suits your requirements. One piece of information that you have to manage is the details of the software versions.

Another example is when you’re using licensed software. The software will be licensed to a particular person or company, and the license will be valid for a certain period of time. Such information becomes the attribute you have to manage. Now that you know what configuration management is, let me tell you a little about how it’s done.

Configuration Management Database

An easy way to manage information on configuration items is by using a configuration management database (CMDB). A configuration management database is just like any other database that stores data, but it specifically stores information related to configuration items.

Configuration Management System

Configuration management isn’t easy. You have to take care of lots of tasks, such as tracking the data and adding and modifying configuration items. To make configuration management easy, you can use a configuration management system (CMS), which is software that helps you manage your configuration items. A typical CMS provides functions for storing and managing CI data, auditing configuration, making changes to the configurations, and so on.

Now that you know what configuration management is, let’s talk about asset management.

Asset Management

In generic terms, anything that’s useful is an asset. If you own a house or a property, that’s an asset for you. So is your car or your phone. When it comes to an organization, anything that’s useful to the organization is an asset. Assets can be capital, office property, the servers locked in your highly secured server room, and so on. But IT assets aren’t limited to physical or material things. The knowledge stored in your employees’ brains is also a valuable asset to your organization.

So, basically, tracking and managing the assets of your organization throughout its life cycle is asset management. The main aim of asset management is to create processes and strategies that help in managing assets properly. The asset management process starts right from the moment of acquiring the asset until disposing of the asset.

For example, let’s say you have an organization that builds and manages web applications. As part of this, you own some servers that you host the web applications on. You also have some databases where you store data for your clients. In this case, your asset management process starts from the time you bought the servers and the databases. You have to manage the buying, maintenance, and inventory costs. Along with that, you also have to take care of regular updates, audits, security implementations, and any changes that you make. This asset management goes on either until the assets are damaged or until they stop being useful to your organization and are disposed.

Asset management directly involves finance. You have to consider the inventory, governance, and regulatory compliance along with the financial aspects in asset management.

Why Do You Need Asset Management?

Asset management helps you understand your financial flow and how to efficiently plan your finances. You can easily track your asset throughout its life cycle. This helps you analyze incidents if something went wrong. Management of assets improves your assets’ quality and performance, which helps your business.

The asset management process helps you stay compliant with various rules and regulations. This improves the quality of your business and also saves you money on audits and fines. Because asset management lets you track your assets, you can plan more efficient strategies for operations.

Configuration Management vs. Asset Management

Now that I’ve explained each of these terms, I hope you understand what they mean. At some point, you might have felt that they were the same. To eliminate any lingering confusion, let me highlight the differences between them.

Asset management is managing anything valuable to your organization. You can consider configuration management to be part of asset management. Configuration management mainly focuses on managing configuration items and their attributes. These attributes mainly affect the delivery of the service.

In the case of asset management, it’s more of a financial perspective. You track the asset to understand the financial flow and need for that asset throughout its life cycle.

To understand the difference, let’s take an example of a hardware component that you’re using—let’s say, a database. When you’re using a database, the database itself becomes an asset. You have to manage the maintenance, track the asset, conduct audits, and so on. This is asset management. The same database will have software versions. Keeping track of the software version, updating it, and tracking which other components it works with becomes part of configuration management.

Configuration management and asset management might sound the same at a high level, but they have different purposes and are implemented differently. Understanding such terms with the help of an example really makes it easy to understand the differences, hopefully, the explanations and examples here have helped you.

Author

This post was written by Omkar Hiremath. Omkar uses his BE in computer science to share theoretical and demo-based learning on various areas of technology, like ethical hacking, Python, blockchain, and Hadoop.

DevOps Tool CHain

What Is a DevOps Toolchain and Why Have One?

DevOps is not a technology, it’s an approach. Though there’s flexibility in how to use it, there’s also the added responsibility of using it in the best possible way. The whole idea of DevOps is to make the software development process smoother and faster. And one of the most important decisions needed to achieve this is to decide on the right toolchain.

So in this article, I’ll tell you what a DevOps toolchain is and why you should have one.

What Is a DevOps Toolchain?

The whole DevOps practice stands on two main pillars: continuous integration and continuous delivery. This means that the changes and upgrades to a product must be integrated at greater frequency, and they should be available to the users at greater speed. A DevOps toolchain is a set of tools that helps you achieve this. But why are multiple tools needed? Why not just use one? That’s because DevOps is a practice that has different stages. To help you understand this, I’ll take you through the different stages of a software development pipeline that’s based on a DevOps approach and review what tools you can use.

Planning

The first step of doing anything is planning, and that holds true for DevOps as well. Planning includes the personnel inside the organization as well as the clients. Both need to have a clear understanding of what they want to build and how they are going to do it. Therefore, transparency plays an important role. You can use tools like Slack, Trello, and Asana for the planning stage.

Collaboration

The beauty of DevOps is that it requires multiple teams to collaborate and work together for efficient software delivery. Once the planning is done, you need to focus on collaboration. Collaboration happens between people from different teams, who might have different working styles or live in different time zones. Easy collaboration requires transparency and good communication. Some of the tools available for collaboration include Slack, Flowdock, WebEx, and Skype.

Source Control

Source control aka version control means managing your source code. In DevOps, where there are frequent updates to the source code, it’s important that you handle it carefully. This means you need a tool that can manage the source code and make different branches available as required, especially when multiple teams are working on a single product. Some of the most popular source control tools are Git and Subversion.

Tracking Issues

You should also be ready for issue occurrence. And when it comes to issue handling, tracking the issue plays an important role. Issues should be tracked in a transparent way that provides all the necessary details required to properly resolve them, and improved tracking results in faster resolution. You might want to consider using tools like Jira, Zendesk, Backlog, and Bugzilla.

Continuous Integration

This stage, as mentioned earlier, is one of the most important parts of the DevOps practice. This is the stage where modular code updates are integrated into the product to make frequent releases. It’s commonly known to developers that the code doesn’t always work smoothly when it makes it to production. You need a tool that helps with easy integration, detecting bugs, and fixing them. Jenkins, Bamboo, Travis, and TeamCity are some of the most popular tools.

Configuration Management

When developing a product, you will have to use different systems. Configuration management tools help you in maintaining consistency across systems by configuring all the systems automatically for you. They basically configure and update your systems as and when required. The configuration management tools that are heard of quite often are Ansible, Puppet, and Chef.

Repository Management

DevOps teams work together to release updates as soon as possible, and when multiple teams are working on them, there will be an update every day or maybe even every hour. With this frequency, it’s important to have a tool that manages binary artifacts and metadata. The repository management tools help push the product or a part of the product from the development environment to the production environment. Some well-known tools for repository management are Nexus and Maven.

Monitoring

Monitoring helps you understand how good or bad the release was. When there are frequent updates to your product, you can’t expect every release to perform well. Sometimes certain releases break the product, create security issues, decrease the performance, or bring down the user experience. The best way to understand what your update has resulted in is by monitoring it. Monitoring tools help you decide whether your release needs aid or not. You can use tools like Sensu, Prometheus, or Nagios.

Automated Testing

You’d for sure want to test your code before making it available to the users. When continuous delivery is the goal, manual testing would slow down the process. Automated testing makes the testing process faster because the tool does the testing, and the computer is faster than a human being. Also, there is no chance of human errors. But you have to make sure that the automated testing tool you choose is efficient and reliable because you cannot afford to have any mistakes here. A few tools you can choose for automated testing are QTP and TestComplete.

Deployment

This is the stage that actually delivers your product and its updates to the end users, and there are a few things that may go wrong here. The main purpose of deployment tools is to make continuous and faster delivery possible. Some of the most popular tools used for deployment are IBM uDeploy and Atlassian Bamboo.

Now that you understand what a DevOps toolchain is and which are some of the most used tools in the industry, let’s understand why it’s important to have a DevOps toolchain.

Why You Should Have a DevOps Toolchain

A DevOps toolchain is needed to maximize the positive outcome of DevOps practice, and it’s achieved when you choose your toolset wisely. A wisely chosen DevOps toolchain will show how the DevOps approach helps you build high-quality products with fewer errors and enhanced user satisfaction.

The first advantage of using a DevOps toolchain is that it decreases the defects and increases the quality of your products. Because of features like automated testing and error-checking deployment tools, there is also less room for errors. This is good for your business and the reputation of your company.

The second advantage is that a DevOps toolchain helps you innovate your product faster. Because the toolchain results in faster planning, building, testing, and deploying, you have more opportunities to innovate. The more innovative your product is, the more business you get.

The final advantage is related to incident handling. The toolchain helps you identify and manage major incidents. Doing so facilitates finding solutions to the incidents faster and letting the respective team know about the incident. This helps improve the support and quality of the product.

In Conclusion

Now that you’ve read about what the DevOps toolchain is and why you need it, it’s time to choose which ones are right for you. Even though I’ve mentioned a number of tools for various purposes, the ones you pick will differ based on what best suits your use case. There’s no universal toolchain that works best for everyone. You’ll know what’s best for you only after you understand your requirements and then choose the tools accordingly.

Author

This post was written by Omkar Hiremath. Omkar uses his BE in computer science to share theoretical and demo-based learning on various areas of technology, like ethical hacking, Python, blockchain, and Hadoop.