How to automate data access and collection 

Data access is the first step for all data analysis, whether you're creating a simple report for your monthly meetings or building complex machine learning models. But doing it manually is time consuming and often requires technical expertise in SQL and APIs that not everyone has.

Consider the numerous data sources your business relies on, from your customer relationship management (CRM) system to accounting software. Each one contains valuable but often siloed data. Gathering information from these disconnected sources usually means that people spend countless hours manually copying and pasting data between spreadsheets or resolving CSV imports. 

What’s more, traditional data access methods tend to require a solid understanding of SQL and APIs, making it difficult for non-technical users to work with them. Complex data structures, varying formats, and incompatible systems add to the frustration and inefficiency for data workers.

Fortunately, a little automation can bridge the gap between your data sources and the platforms where data is consumed and analyzed. With tools like KNIME you can simplify the entire data access and collection process. Here’s how:

KNIME Analytics Platform lets you connect to 300+ data sources with minimal coding knowledge. Whether you need to get data from SQL databases, NoSQL stores, spreadsheets, cloud storage like Amazon S3 and Google Cloud, Databricks, Snowflake, or REST services KNIME has a library of pre-built connectors that can pull-in your data quickly. 

There’s no real limit to how many data sources you can integrate into one workflow. 

Need SAP and market data in the same place? No problem. Need to pull in data from the cloud, on-prem, and then use an API? No problem. This means you can bypass the manual, error-prone process of data collection and instead create a repeatable error-free process that saves you time and energy. 

After pulling in all the files that you need to work with, you can easily standardize, blend, and transform these data sets and build the rest of your analysis with KNIME’s intuitive visual workflows.

Once you’ve set up your data connections, automation can help you ensure that your data is always up-to-date and ready for analysis without manual intervention. Besides, automation gives you the freedom to scale the number of sources you get your data from. The manual process that worked when you had 5 data sources will not work when you have 50 or 100 or 500, but an automated process can handle any number of sources with ease.

KNIME workflows also automatically apply the transformations you've set up to the new data, updating your reports without any extra effort. There's no need to reconnect to data over and over again to build the same report or rely on Excel macros to format it correctly. 

You can build your data workflow once, and execute it forever.

Automation of KNIME workflows is available through a KNIME Team plan and can be achieved with schedules and triggers. 

1. Schedules: You can configure your KNIME workflows to run at specific times or intervals. For example, you might schedule a workflow to pull in new sales data from a database every morning. This ensures that your data is always current, and you’re never working with outdated information.

2. Triggers: Alternatively, you can set up workflows to run automatically when specific events occur. For instance, a workflow could be triggered to ingest new data every time a new entry is added to a CRM system. This event-driven approach is highly effective in environments where data changes frequently and requires immediate action. Triggers also make integration with other systems and data sources seamless.

With KNIME’s Team plan you only need to pay for what you use and you can cancel your subscription anytime. You can scale your usage up or down according to changing workloads, avoiding the expense of full-time licenses.

Connecting to the data you need for your analysis can take up hours of your workday. But it doesn’t need to. With KNIME you can speed up and improve the way you work with data — connecting to disparate sources, integrating with third-party information systems or new technologies as needed, building analysis of any complexity level using that data, and automating the whole process. 

Setting up automated data workflows not only saves time but also reduces the risk of errors, letting you focus on what really matters — deriving meaningful insights from your data to make more informed decisions.

Try it out for yourself. Start automating your workflows today with a one-month free trial.