It’s time to move on from the ‘Manual v Automation’ debate and focus on more critical issues. That’s one major change COVID-19 brought; it propelled the adoption of automation beyond everybody’s predictions. So, organizations whether startups or enterprises want to elevate their readiness to build systems that can integrate quickly and efficiently. After all, interoperability is a key differentiator in data management. In the following post, I share a quick run-through of the factors that make it imperative to embrace advanced data integration processes.
More Cloud, More Systems & More Data
The arrival of the cloud brings many conveniences and efficiencies, but can also pose challenges for cohesion with in-house data and applications. Enterprise data integration is designed to support the new world of hybrid IT, connecting both legacy on-premises systems and newer, cloud-based apps. Consider this, 95% of businesses struggle with unstructured data and that’s because there are too many platforms integrated.
Strict Regional & Global Regulations
Compliance is significantly important for better focus and thus is a priority for any business these days. But at the same time, these businesses also face complications that arise due to disconnected or distributed data. The latest data privacy regulations that are becoming the new norm are the EU GDPR and CCPA. organizations now use enterprise data integration to track apps and systems across geographies easily. It also helps them stay compliant with all the relevant regulations.
Linear Scalability in Real-Time
An ideal data management system should be able to scale in a linear trajectory. This allows the system to manage millions of secured micro-databases at the same time. Such a management system can be deployed either on-premise or on the cloud as an iPaaS, data hub architectures, in data mesh, and data fabric.
K2View’s unique approach to data integration includes processing, integrating, and delivering data by the said business entity. Here, the data integration tools can be used by data engineers to develop and maintain scalable data pipelines, be it for an operational or an analytical workload. Their fabric is already popular for capturing data for every business partner in an exclusive micro-DB while managing millions of such micro-DB containers effectively.
With such proven expertise, K2View comes with real-time speed and supports different operational use-cases, in which every millisecond counts. When in-memory computing joins hands with a company’s patented micro-database tech and comes with a distributed architecture, you can deliver unmatched source-to-target performance easily. As a result, it ensures faster time to value, enhanced productivity, and greater visibility.
Improve Partner and Customer Relationships
Milestone Systems are a leading video management service provider. Initially, they were spending a lot of their time and resources on entering data manually across two different systems. This left their account executives stressed out as they had less to no time left to focus on building relationships. To solve this challenge, we help them link Salesforce and Microsoft Dynamics together. Thus allowing Milestone Systems to greatly benefit from system integration. Their account executives now spend their time analyzing and using numbers instead of recording them on a system.
With system integration, data can be automatically shared and exchanged between different systems. With this service, Milestone Systems can also make the most of the Sales History Add-On. As a result, we have been successfully able to provide them with more opportunities, better relationships along with impeccable business growth.
Need for Less Redundant Data
Let’s look at a hypothetical situation. Say you have just 60,000 files. Would it be easier to look at each one or all of them at the same time?
Every time you collect data, there is always some redundant information that comes along with it as there can only be several preferences. Let’s look at an example of redundant data. A Sales company uses SalesForce for the sales organization and customer support uses ZenDesk for answering user queries and support questions. It can easily become chaotic if these data pools are not merged. Moreover, platforms like SalesForce duplicate data and contacts every time sales reps enter data.
A smart data integration workflow resolves such glitches in real-time and that too with minimum manual interference.
Minimize Inconsistent Data
You can get inconsistent data in several ways -every time you collect text, images, or videos from your users. All these files come in different formats, file names, specifications, and several other inconsistent factors. This inconsistent data creates several problems and it becomes considerably hard to analyze this data in case you are looking for something.
This has been challenging for IT professionals as they feel that they cannot use the mass of this data to its full potential. Data integration can be used to make the specifications and formats more consistent. This will eventually enable users to find what they need and use the collected data more efficiently.
Accelerate Lead Generation
Organizations can implement effective cloud data integration to gain several benefits. Some common enhancements that come your way include a full picture of the KPIs or key performance indicators along with regulatory compliance efforts, customers, financial risks, production & supply chain operations, and other business processes as well. You can integrate advanced analytics and BI (business intelligence) business reports in the data feed on transaction processes and systems that run data warehouses, business apps, and data lakes. Pooling everything together in a single interface helps you with business development goals as it clarifies the shift in demand and market trends as well. Contrary to this disorganized and inconsistent data makes it impossible for you to act on any opportunities.
In the present day scenario, new apps and data sources are making a routine entry into the enterprise fold. You can build a relevant enterprise data integration solution with a strong architecture and help businesses not only incorporate their data but also manage and use it for better business analytics and reporting. All it takes is the right data management landscape. Which one do you prefer?