With a huge amount of data from various sources and systems, modern-day enterprises needed to handle the five major V’s of data as value, variety, velocity, veracity, and volume effectively. For this, the primary need is for a solid integration tool with which an enterprise can extract the most relevant information and deal with the data with the right velocity on time, improve the integrity of data, and process a huge volume of data in a matter of seconds. This article will discuss some of the ways and tools for data integration that will be useful in your business database management.
Faster And Better Time-To-Value
Nowadays, enterprises tend to use approachable tools to create a single source of truth for data, which can further expedite the internal processes and fetch valuable insights faster. For example, big corporates’ legacy data may take a week or so for migration, which can be done in a matter of hours with the data integration tools. Similarly, huge chunks of financial or healthcare data integration can be done in a time-critical manner using integration tools.
To Make Well-Informed Decisions
Smart data integration methods and tools will let businesses manage, measure, and monetize their decision making based on quality data analysis. With the help of integration tools, the users can now directly access the day they need without constantly requesting it from the IT department. Whenever needed, the stakeholders and decision-makers can get a complete view of the data and strategic insight to gain an edge over the competitors.
Improve Revenue Through Quality Data
As we can assume, data quality directly correlates to business decision making for a positive or negative outcome. When the data analyzed is clean and insightful, studies show that business can improve their revenue by 60% with a high-quality database. With cleansed and relevant data, business decisions can be sculpted better for meeting their objectives without being blocked by data quality. However, the cloud-based tools for data quality management offer very secured access to data from anywhere and facilitate easy disaster recovery.
Choosing The Right Data Integration Tools
While considering the data integration tools for enterprise use, it is important to ensure that the solution you choose can offer all the needed features to facilitate the data journey. Here are some of the fundamental data integration tools based on the most common business use cases. For any data integration and data migration needs, you can consult with reliable providers like RemoteDBA.com.
Bi-Directional / Multi-Directional Synchronization Of Data
In many typical data use cases, the data used not only should be transformed into one destination, but it also needs to be updated in various systems by maintaining consistency and authenticity throughout the network. In this case, a good integration tool must offer a very accurate synchronization between various connected systems.
Automation of Workflow
As we can see, data integration is not a one-time task to accomplish. All incoming data sets need to be constantly cleaned, synced, and be available to the users. A trigger-based workflow will let the data analysts automate the tasks having repetitive nature and simplify the overall integration. The users can quickly schedule the workflows and run them at specific set times through triggers while a specific criterion is met.
Faster Data Processing
The competitive businesses may assign more time and resources for scaling out and other revenue-centered decisions if they can be relieving from the time taken for integration tasks. So, replacing this with faster and automated solutions is necessary. An ideal data integration tool needs to cover up this requirement well and process a huge volume of data much faster and efficiently without consuming much time at any stage of the integration. For those industries where analyzing and processing data is critical, like healthcare and finance, integration tools must be able to ease out the tasks by minimizing the latency to an affordable level.
Supporting Multiple Data Source Systems And Various Data Formats
Modern-day enterprises need to work with various formats or data from different sources. They need to include modern and legacy formats and handle all types of data as structured, unstructured, semi-structured, etc. A good integration tool must offer support to all of them to offer a comprehensive solution.
Data Profiling and Cleansing
Data cleansing is a major component of data integration that can identify and sort out the weeds of data stores and ensure that only quality data gets into business analysis. Data profiling also ensures that data analysts use the most updated and real-time information to derive actionable insights and implement strategies. It is an important tool that you can use for your business to get better results. Data profiling will enable you to better target your customers and deliver to them exactly what they need. This is one of the most efficient ways to deliver your products to customers.
Anytime Data Previews
While creating more complex workflows and data models, it is so important that you should get the previews and input and output data at any given node in the flow before executing to avoid any overhead or correction. Feature of data previews must be there on the integration tools for better visibility and flexibility for mappings. It should also enable checking for any issues at different instances and correcting them before tampering with the entire flow.
Once the data is cleansed and updated, business analysts may also need data profiling to extract data statistics, summaries, and insights from the database, which they may utilize for better-informed decisions. Both of these features are necessary for any data integration tools.
All major databases and database engines offer different data integration tools, but the features of each of these may differ. For any data integration project, you may need first to analyze and understand your customized requirements to devise a data integration plan and choose the most appropriate tools to execute it. You don’t need to use the database engines’ exact tools, but all major databases can be integrated with frontline third-party integration tools for this purpose.