What is your business’s most valuable asset? If you said data, you’re right — but only if you can make sense of it. Data connectivity is often the missing link, but it can quickly escalate into a time-consuming, complex endeavor for organizations using disparate datasets, applications, and storage systems.
Organizations must use strategies and technology to overcome these challenges and gain a unified, accurate view of their data — a competitive differentiator in today’s data-driven environment and a prerequisite for automating analytics. Seamless data connectivity also enables business users to solve problems with data insights without having to rely on data engineers or IT teams for support.
What is data connectivity?
Data connectivity is the process of architecting and managing connections within an organization to facilitate smooth integration and ongoing maintenance of data sources and systems. Data connection management requires deep technical knowledge to set up and manage connectors, which act as bridges between diverse and non-traditional data sources.
Why is data connectivity important?
The real value of data connectivity is its ability to help organizations, teams, and business users get a unified and accurate view of data for actionable insights. From a technical standpoint, connectivity is essential for organizations that want to build a flexible, reliable data environment that can adapt to changes and integrate new technologies without disruptions.
Maintaining data connectivity also ensures the adaptability and agility of an organization’s environment — minimizing downtime when changes are made in data architecture. Without it, something as simple as updating a single data component, such as an expired password, would require updates to hundreds of components.
How does data connectivity work?
Data connectivity starts by identifying where data is coming from within an organization, both internally and externally. Then, data connectors are set up to facilitate data exchanges between them using various methods such as protocols, application program interfaces (APIs), and integration tools. Once that’s in place data can be transferred between the connected systems for processing and analysis.
Cloud connectivity
For the growing number of organizations running applications in the cloud, connectivity refers to the strategies and technologies used to connect cloud services and infrastructure with other parts of the IT environment, including communication between cloud-based resources and on-premises systems.
Organizations transitioning from on-prem to cloud environments must balance the maintenance of cloud connectivity while continuing to support legacy systems that are still required for operational continuity. Supporting data connectivity in old and new systems and ensuring they work well together is a common challenge for the 90% of businesses that still have some form of a legacy data stack.
90% of businesses don’t have a modern data stack
Another unique consideration for data connectivity in the cloud is the process of data sampling. When building workflows in the cloud, it’s more efficient and effective to run through a sample of data to make sure you are getting the results you want without moving the entirety of your data and using up costly compute resources. By downsizing large data sets to representative samples, organizations can save time, reduce data transfer costs, and make it easier to identify data insights.
Data connectivity and governance
Managing data connectivity should also be a factor in your organization’s overall governance strategy. That includes managing access to data and how it is handled across connected data sources to ensure the process meets legal and security requirements.
Governance is especially important in an environment where there is external connectivity. In this scenario, private data handling can be used to securely manage sensitive data without moving the processing and egress costs that come along with it.
Automation can improve governance further by pulling in data and kicking off workflows automatically, helping to ensure processes are consistent, reliable, and compliant.
Solutions for data connectivity
Data connectivity solutions enable organizations to connect and integrate disparate data sources — making data accessible, more accurate, dependable, and easier to analyze. More organizations are choosing modern connectivity solutions to replace traditional integration approaches that involve custom coding and manual maintenance. Newer technology solutions for connectivity are easier to set up, enable rapid access to data, and reduce the time engineers spend on maintenance and troubleshooting.
If your organization is ready to move on from manually building custom code connections to a modern approach to connectivity, it’s important to look for the following features.
Scalability
As the volume of data and data sources grow, organizations need a solution that is scalable enough to accommodate future changes and demands for future connections. A flexible solution with interoperability is also important to minimize costs and adapt to future advancements in technologies like AI and machine learning without requiring complete overhauls.
Automated, out-of-the-box connectors improve scalability and reduce the time and resources needed to build custom solutions, which impacts time to value.
Security
To reduce the risk of connecting disparate internal and external data sources, look for a solution with strong authentication and encryption protocols that protect against breaches or unauthorized access.
Look for automated capabilities that will increase data trust and security by reducing manual tasks that are prone to errors.
Reliability
The best performing data connectivity solutions will ensure high availability of data and minimal downtime.
Easily connect your users and your data with Alteryx
The Alteryx AI Platform for Enterprise Analytics is the glue that connects your business users with your data infrastructure. With one of the most robust lists of connectors in the market, Alteryx allows solvers of all skill sets to better utilize best-in-class technologies like AWS, Databricks, Snowflake, Azure, and more.
By centralizing data connections with Alteryx with the Data Connection Manager (DCM), your analysts can be more productive and efficient. The DCM also provides a unified secure vault that stores user passwords and credentials related to data connections. It rethinks connection management by moving credentials from Input/Output (and other) tools and into local encrypted storage.
The online health platform BODi faced a significant challenge with siloed data across different storage and processing technologies that was impacting its ability to gain a holistic view of customer interactions.
They overcame this by centralizing data ownership with a single analytics team and redesigning their data architecture around Snowflake’s Data Cloud™. Then, integration with Alteryx enabled easy data access and transformation, facilitating self-service analytics across the organization.
The new system enabled a 360-degree view of the customer, improved efficiency in executing data-driven marketing campaigns, and empowered more precise customer behavior analysis and forecasting.
This seamless and connected solution reduced infrastructure costs by 33% and resulted in a 240x improvement in query performance.
Fender also worked with data from multiple sources, including SQL Server, Excel, and Google Sheets. By integrating Alteryx with AWS and Tableau, the analytics and automation team could manage large datasets more efficiently, improving query runtime and reducing Tableau reports’ load time from minutes to seconds. The time savings allowed the team to gain deeper insights and provide more impactful business value.
Next steps to modernize your data connectivity
Data connectivity is an essential function of the modern data stack. Data management and analysis depend on seamless connections between the data systems and applications used across the organization. When that’s achieved, the true value of data can be realized to improve decision-making, optimize operational efficiency, reduce costs and risks, and maintain a competitive advantage.
To learn more about how to modernize data connectivity, you can watch this webinar on-demand, “Automating Analytics: Uplevel Your Data Connectivity,” and check out the Alteryx integration page to better understand how easy it is to get more value from your data sources and technology investments.