In today’s fast-paced world, data has become crucial for businesses to make informed decisions. However, data can pile up so quickly that it often becomes more of a burden rather than a helpful asset. A holistic approach to data involves bringing together data from various sources, analyzing it comprehensively, and taking strategic actions based on the insights gained. By embracing a holistic data approach, businesses can unlock the full potential of their data and drive growth and success.
What is a holistic approach to data?
Holistic means focusing on whole, complete systems, instead of focusing on their separate pieces. Holistic data refers to the practice of looking at data in its entirety, rather than just focusing on individual pieces of information.
By getting unified data from various sources, businesses can gain a more complete understanding of their operations, customers, and market trends. This approach can lead to numerous benefits, including improved decision-making, increased efficiency, and enhanced insights. However, integrating data can also present challenges, such as data quality issues and the need for specialized technology. Fortunately, there are technologies available that can enable holistic data integration, such as integration platforms and cloud-based solutions. By embracing a holistic approach to data through integration, businesses can gain a competitive edge and stay ahead of the curve in today’s data-driven world.
Why is holistic data important in 2023?
the bigger picture and the relations between the different parts of it. This approach allows us to significantly reduce the time spent on analyzing and organizing data.
The benefits of the holistic data approach include simplifying business systems, improving data accuracy, and smart automation. As a result the efficiency of the teams involved significantly increases. By integrating data, businesses can avoid data silos and gain a complete overview of their operations.
Why to integrate your data:
- Get the bigger picture and how its parts interconnect
- Reduce time and efforts for processing data
- Simplify workflows and business processes
- Improve data accuracy and quality of insights
- Boost efficiency
- Avoid silos and bottlenecks
- Get a complete overview on your data and operations
- Obtain competitive advantage
In 2023 businesses continue to adopt digital transformation and automation at full speed. Staying competitive is becoming harder and harder and businesses cannot thrive without leveraging their data to the maximum. This is why taking a holistic data approach is essential.
Challenges for integrating data
While integrating data can bring numerous benefits to organizations, there are challenges for adopting unified data, as well, that often make leaders hesitate. One of the main challenges of integrating data is dealing with the different formats, structures, and quality of data from various sources. This can result in data inconsistencies, duplication, and errors. Additionally, integrating data from multiple systems and sources can be time-consuming and resource-intensive, requiring significant investments in technology, infrastructure, and personnel. Another thing to consider is ensuring data security and privacy, especially when dealing with sensitive information.
Main challenges for integrating data:
- Different formats of data that needs to be integrated
- Inconsistent quality and structures of data from various sources
- Duplications and errors
- Investments in integration technologies
- Data security and privacy
- Time and resources needed for integrating data
These challenges often prevent managers from taking the leap to a holistic data approach. However, with the correct strategy and technology potential problems can usually be avoided. Integration platforms are advancing quickly and offer a bunch of solutions, depending on the specific scenario. All it takes is carefully planning and choosing the right tools.
Technologies that enable holistic data integration
Technologies that enable holistic data integration play an essential role in achieving a comprehensive view of an organization’s data. These technologies enable organizations to connect and integrate data from different sources, including cloud-based applications, legacy systems, and disparate software tools, ensuring data consistency and accuracy.
Let’s have a quick look on the major integration technologies used:
- Extract Transform Load (ETL) – this is one of the most common technologies for data integration. It consists of the processes of taking (extracting) data from one system, changing or transforming it in a suitable format, and then inserting (or loading) it into another system. The method allows multiple transformations of data and is quite popular in integration platforms. For example, ZigiOps automates the ETL process and does all transformations in the background. This means you do not need to worry about different data formats. If one of your systems uses XML and the other one JSON, for example, ZigiOps will transform the data automatically and send it to the destination system in the correct format.
- Enterprise Information Integration (EII) – this method provides data on demand, creating a virtual layer or a business view of relevant data sources. The idea of EII is to get a large set of heterogeneous data sources to appear to a user or system as a single, homogeneous data source.
- Еnterprise Data Replication (EDR) – this is the process of generating numerous copies of enterprise data and storing them in multiple locations. EDR allows replicating complex data from disparate sources and loading it to target destinations in near-real-time or in regular intervals.
- Data Visualisation – this means representing data through the use of graphics, such as charts, plots, infographics, and animations. Analytics and reporting tools often have built-in functionality to quickly visualize data.
- API (Application Programming Interface) – APIs offer direct access to data, but specialists need to connect them properly, test and monitor them to be able to have a stable integration through them.
These technologies allow data to be collected, processed, and analyzed from various sources, systems, and applications. Based on these methods, there are many integration platforms and tools available on the market. Each of them has unique features, pros and cons. This is why organizations need to carefully consider which integration tool to use, based on their specific needs.
By embracing integration and the holistic data approach, organizations can eliminate data silos, reduce manual data processing, and improve data quality and governance. This leads to better decision-making, increased operational efficiency, and improved customer experiences.
Examples of integration cases helping for holistic data approach
With unified data, businesses can identify patterns and trends that were previously hidden, enabling them to make data-driven decisions. Additionally, holistic data reduces the risk of errors and inconsistencies, as all data is stored in a central location and updated in real-time. While integrating data can be challenging, the benefits far outweigh the costs, and there are many examples. Here are a few common ones.
- Integrating data in helpdesk and IT service management
When there is a ticket that requires the attention of the helpdesk team, it is very helpful to have all the data for the client – previous requests, issues that required development, problems with their orders, billing, communication, etc. Integrated data from all sources for this particular customer would allow the helpdesk agent to serve this client the best way possible and much faster at the same time. This boosts client satisfaction and improves the company rating.
- Integrating data in monitoring
Organizations often use several monitoring tools to track all of their systems, hardware, virtual machines, applications, etc. When the information from these monitoring tools is disparate, it is difficult to track alarms and recurring issues and prevent serious problems. Integrated data from all monitoring tools helps responsible team members react quickly and without letting issues affect the end user.
- Unified data in CRM
Customer relationship management systems are an essential part of the ecosystems of companies. These platforms track all customer orders, renewals, communication, received campaigns, customer service requests, etc. Having the right data from DevOps, service desk and marketing together with the CRM data, would help the sales team manage customers in the best possible way. This results in more qualified leads and more sales.
- Integrating DevOps data
The development team needs to have relevant and timely information about software bugs and issues that clients encounter, as well as feature requests. Based on that information they can prioritize and handle their tasks properly, so that bugs are fixed quickly, and the most desired features are developed first. Also, new releases and new products are very important for the advancement of the company and the overall bottom-line.
To determine your own scenario, and embrace a holistic data approach in your organization, you can start by asking the involved stakeholders some questions. For example:
- how they use the data,
- who needs access to it,
- what do they need to know,
- what would help them handle issues faster,
- what would improve their processes,
This helps form your own specific requirements and find out what you need to do to adopt a holistic data approach. You can create a standard for your data that fits your business needs. Consider the entire data lifecycle and make sure that data is clean, accurate and reliable.
This kind of processes and smart automation empower organizations to make informed decisions, drive innovation and stay competitive.
How ZigiOps can help?
ZigiOps integration platform provides lots of opportunities for taking a holistic data approach. It is completely no-code and allows even non-technical users to create integrations in a few clicks. ZigiOps has out-of-the-box integration templates, that you can use immediately, and customize them per your needs. Here are the ways that ZigiOps helps avoid the challenges and embrace unified data without the usual hustle:
- 100% code-free – no coding or API knowledge is required to work with ZigiOps.
- Enterprise security – the integration platform strictly follows security best practices, it also does not have a database and does not store any information.
- Scalability – ZigiOps is highly scalable, and integrations can be upgraded and updated per your specific needs.
- Easy customizations – each integration is easy to customize and can handle even the most complex integration scenarios.
- Automatic data transformations – data formats are transformed in the background and you do not need to worry about any inconsistencies.
- Advanced mapping capabilities – you have complete freedom to map the data the way you need to, including complex conditions.
- Expressions and filtering – lots of freedom to create RegEx expressions and filter the incoming data per your specific needs.
- Standalone solution – ZigiOps is not a plugin, it connects systems via APIs and you do not need to do any changes within your instances.
- Ready-to-use integration templates – the integration tool provides templates for common integration scenarios that you can load in a click and then customize if needed.
- No limitations on number of transfers, syncs or users – you do not need to worry about reaching the limit for transferred entities or syncs.
You can integrate your systems in a few clicks and start benefiting from unified data right away. Book a free demo and see how it works.
Data is one of the most important assets of a business. The quantity of data is becoming unimaginable. Quality is on the other hand hard to achieve. How businesses deal with data? It is usually scattered across departments, teams and partners. Analysts of data spend hours and days each week cleaning the data and organizing it.
So, if you’re looking to stay ahead of the curve and drive your business forward, it’s time to take a closer look at your data strategy. Don’t let outdated systems or siloed information hold you back from achieving success. Instead, embrace the power of holistic data and unlock new opportunities for growth.
Integrating data is not without its challenges, including data quality issues, compatibility problems, and privacy concerns. To overcome these challenges, organizations can leverage technologies such as cloud computing, APIs, and data integration platforms. By doing so, they can ensure that their data is accurate, secure, and accessible in real-time.
With the right tools and mindset in place, there’s no limit to what you can achieve with your data. From identifying new market trends to improving customer satisfaction levels, every aspect of your business will benefit from a more comprehensive approach.