Let’s take a quick run through everything to do with data ingestion, including how to choose between all the great data ingestion tools out there.
The key to making reliable data-driven decisions is maintaining a high-quality data intake. If your data is messy, scattered, or incomplete, the conclusions you draw from it will be, too. A carefully-planned data ingestion process, where data is properly validated, stored, and secured, will save you time and money and enable fast, smart decision-making.
When receiving data from customers, partners, or suppliers, you naturally come across a wide variety of schemas. Customers will call headers differently, format entries in a different way, or simply store required information in multiple sources.
This makes manual data imports from a range of sources a time-consuming, tedious, and expensive task prone to human error. In our data-rich world, data ingestion tools are becoming increasingly popular. These tools automatically extract data from a range of sources, convert it into the format you need to work with, and transfer it all to the desired location. Data ingestion tools ensure that clean data flows from the original source into your data, reporting, and analytics system.
That might all sound good in theory but how can you know if data ingestion tools are really relevant for you in practice? Let’s walk through some of the key benefits to help you figure that out.
Improve data quality
Messy data is no good to anyone. The top data ingestion tools can automatically streamline and sort your data before it gets stored in your database.
More effective data management
As data ingestion tools clean your data on its way into your database, there are far fewer inaccuracies or duplications which leads to more efficient data use overall.
Speed
Data ingestion software allows you to automate your processes which means you can extract data from sources and ingest it into your data system quickly. As minimal human oversight is needed, and your team’s time can be better spent on other tasks.
Scalability
Data ingestion only really becomes a challenge when your organization scales up. If you’re working with a low number of customers, then manually ingesting data is quick and easy. However, as soon as your data volume increases, so does your workload. That’s where data ingestion technologies really show their value.
Cost-effectiveness
As data ingestion tools allow you to automate your processes, you save time and money you would otherwise spend on repetitive manual processes.
Easy to use
Data ingestion tools like nuvo are built to be used by anyone, not just those with existing tech knowledge. User-friendly interfaces with simple, intuitive functionalities are easy to master and don’t require long, boring training sessions. Win-win.
Faster customer onboarding
For any business, but particularly low-touch SaaS, it’s important to give the customer value as soon as you can. Integrating real-time data ingestion tools into your onboarding flow helps you process new data immediately which speeds up the customer journey and reduces churn.
Simplified data cleansing
When you work with data, you need it to be clean and easy to transform. Choosing the right data ingestion software automates data cleansing and simplifies data transformation processes meaning you can trust your data from day one.
Quicker data transformation
Real-time data ingestion removes the need for batch-processing. Using a data ingestion tool means that data can be cleansed, validated, filtered, enriched, and normalized as soon as it arrives.
Faster, smarter decisions
As data ingestion tools allow for immediate inbound data transformation, internal teams can make faster decisions and generate more leads.
Focus on your business
As inbound data can be transformed so fast, it allows teams to move away from validating and cleaning data back to tasks that directly impact the bottom-line. The ROI on data ingestion tools quickly becomes clear.
If you’re convinced and ready to choose a data ingestion tool, there are some key factors to consider when making your choice. You need to think about interface, format, security, interoperability, frequency, and user-friendliness.
Interface
Is your data ingestion process customer-facing, or will your in-house experts handle it? These approaches call for strongly differentiated user interfaces and allow a different level of complexity.
Format
What type of data do you have to ingest? Does your data have a somewhat repetitive structure and can be fully automated at some point, or do you have heavily different data schemas to ingest?
Security
Are you working with highly sensitive data? In that case, you clearly need to identify who can access your data and at what point.
Interoperability
How well does your data ingestion process play with others? Make sure the one you choose is compatible with all your data sources.
Frequency
Do you need real-time data ingestion or would you prefer to use a scheduled, or event-based approach? If real-time processing is key, look for software that performs that function.
User-friendliness
In most cases, it’s important to save engineering resources for more pressing tasks. By choosing a data ingestion tool that’s easy for non-technical team members to use, you’ll save everyone a lot of headaches and use your time and team more efficiently.
Let’s discover what are the steps of importing data into your desired destination and why these steps are so important.
Data Importing
The first step in a good data ingestion process is importing the data from various sources such as databases, files, or APIs. It's essential to ensure that the data is accurate, complete, and relevant to the business needs. This step involves identifying the source, connection, and format of the data, and importing it into the system.
Data Mapping
Once the data is imported, it's essential to map it to the target schema or format. The mapping process involves aligning the data fields from the source to the target schema. Mapping ensures that the data is consistent and in the right format for analysis or processing.
Data Validation and Cleaning
Data validation and cleaning are critical to the data ingestion process as they ensure the data is accurate, high quality, complete and trustworthy. This part involves removing any inconsistencies, errors, or duplicates in the data, and verifying it against predefined rules, constraints, or standards. This final step makes certain that the data is suitable for further analysis or processing.
And there you have it! We hope that you have now a much better understanding of the data ingestion process and can make an informed decision on the tool you need. If you’d like to learn more about how to create a seamless data ingestion experience with nuvo, contact us today and get a free demo.
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