According to Gartner research, organizations lose approximately $15 million on average per year due to poor data quality. Staying ahead in today’s environment requires access to reliable data at a moment’s notice. Smart businesses invest the time and resources needed for effective data integration, which is an essential part of creating successful analytics programs that drive overall success. Data integration solutions aid in transferring data from the source to the destination, accelerating and streamlining the process.
Finding the right people to complete projects involving data integration can be expensive and challenging. Using many coding languages and frameworks adds another level of complexity. Upskilling resources to get data into and out of source systems becomes more difficult.
Moreover, several businesses manage multiple data marts across various cloud ecosystems. It is difficult to swiftly and simply integrate data across platforms. The solution must integrate all the data, which will make it possible to switch over smoothly to an enterprise-grade platform. Additionally, it gives you access to all the data required for efficient analytics.
Maintenance tasks need to be carried out throughout the data lifetime to keep your data integration current. This entails tracking how your data integration tools are being used, leveraging outside schedulers to conduct your processes, configuring new users, and carrying out upgrades.
All this and more can be done with a data loader. Chainsys’s dataZap is a data migration and integration platform. It requires no code, no DevOps, and no infrastructure. It comes with 9000+ smart data templates and is certified by both Oracle & SAP.
5 ways dataZap can help optimize operations
Listed below are some of the ways that our mass data loader can help your organization reduce maintenance and operational costs.
1. Pay for what you use
You will only have to pay for how much data has been used. You can upload as much data as you need into your data warehouse. But for any integration to be successful you will need to keep track of who is using the data loader and the jobs being executed. dataZap comes with a dashboard that will give you an in-depth analysis of who is using the application and the amount of data that is being processed.
How you benefit – Any project will involve multiple teams and people such as developers, data engineers, analysts, and business teams. With so many people involved you might have to get a subscription for them all. But with the dashboard, you can find out who is effectively using the tool and restrict access to them. This way you can cut down on the costs of subscriptions where the tool is not used.
2. Data validation and reconciliation
Without quality data, any decision that is made cannot be 100% correct. When integrating or updating data, care must be taken to ensure the data is correct and without errors. If done manually human errors are prone to happen. All this can be avoided with the dataZap which comes with prevalidation and data reconciliation.
How you benefit – Any business decisions that the top management makes will have company-wide repercussions. Having clean data uploaded the first time ensures that any analytics or decisions taken will be accurate and make it effective.
3. Visualization and monitoring
To measure the success of any tool you require actionable information. Chainsys’s dataZap has a reporting engine that generates reports on the various adapters’ execution and produces dashboards to understand the actions taken and to be taken. The information in this section will be organized into job name, status, rows processed, start time, and end time. Click on any job to view the work’s attributes, outcomes, and information about the subtask. You will get an error notice if the job fails. On the same page, you may download logs. Users can view the log details without needing additional access to other environments.
How you benefit – In case you have multiple data points that need to be updated in your data mart, you can pause any analytical operations till the data are successfully uploaded. The dashboard will give a notification when all the jobs are completed without the need to individually contact the teams at the site for a status update. Once the data is loaded successfully the analytics program can be initiated automatically.
4. Task scheduling
dataZap data provides the capability to schedule tasks without any external simulators. By scheduling known or repetitive tasks you can free up resources internally and focus on other business priorities.
How you benefit – Following up on our previous example, suppose an analytics operation requires data from various sources and the sources are in different time zones, it is not possible to get the information at the same time. The analytics operation can be scheduled to run when data from all the regions are uploaded successfully and in any time zone. Due to this requirement, the data is regularly loaded and the report is readily available when required.
5. Working in shared environments
Many organizations have shared data and data siloed in multiple environments. Bringing them together into one location is difficult and in many cases costly. dataZap allows working on multiple environments at the same time.
How you benefit – Consider your company is acquiring another company and you want to upload large amounts of data from Salesforce to your system which is SAP. For an analytics need now they also merge multiple data warehouses. Now you can upload all the data into one data warehouse by inviting the other analysts to the dataZap. They can use existing tasks or build their own. This will help reduce costs as you will not need to create new pipelines or go for more third-party integrations.
Get started with dataZap data loader
Are you interested in our data loader into your data integration strategy to help optimize your maintenance and operational costs? Get on a call with our experts for a live demo and how we can specifically help your organization.
Or you can go through our resources to understand more about dataZap and mass data loader
Mass data loader
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