How Proper Data Tool Investment Will Unlock the Power of Data for Every Organization

When it comes to data analytics, machines should be doing the heavy lifting. More and more businesses rely on data analytics to make smarter, more informed business decisions and to stay on top of industry changes amid competitive markets. As a result, data scientists are pushed into extracting, processing, cleaning, and analyzing data from multiple sources on a daily basis for multiple purposes within an organization.

According to research from IBM, data scientists spend 80% of their time searching and cleaning data, rather than extracting insights from it. Organizations want their employees spending less time buried in data, and more time using it to make quick, informed decisions that help businesses grow. Success requires what I call “democratizing data analytics” to enable more employees to make quicker decisions without relying on technical data teams to extract valuable insights for them.

Simply put, democratizing data analytics means equipping teams with business intelligence (BI) or no-code and low-code tools so that the broader tech community gains the ability to realize benefits. These gains include enhanced innovation, additional time to work on priority projects, and accurate processes that are being completed in a more timely manner. Non-technical employees will be able to make informed data-driven decisions themselves and focus on their core responsibilities without having to depend on the data team.

Unlocking Insights

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The proper tools will make the data preparation process 10X more efficient. And efficiency isn’t the only benefit – making data easier to work with is a crucial step in the democratization of data across an organization. Proper adoption and rollout of data tools will lead to benefits for technical and non-technical roles alike.

Businesses want their data science teams spending less time answering one-off questions and data requests, and more time thinking about new, innovative ways to solve pressing business problems. Advanced data collection and analytics tools – like graph databases powered by AI and machine learning – facilitate the automation of mundane or repetitive tasks, freeing them to spend more time on strategic priorities.

With machines doing the legwork, data teams can spend less time on data collection, cleaning, preparation, and aggregation. For instance, data teams can use graph databases to handle relationship queries and perform real-time analytics, making it easier to develop more complex data models. AI and machine learning tools further enhance efficiency by enabling predictive analytics and automating the extraction of actionable insights from data. Additionally, Extract, Transfer, and Load (ETL) tools streamline the data integration process, automate transformation tasks, and improve data quality. By leveraging these technologies, technical teams can shift their focus from routine data handling to addressing more strategic projects.

Boosting Autonomy

When businesses invest in the right data tools, non-technical teams also see a benefit because they no longer have to depend on data teams for access to the data and analytics they need to be successful. They also gain more agency and autonomy in making well informed decisions that are grounded in data.

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Low-code and no-code data tools are two examples of solutions that work to effectively democratize data solutions for non-technical users by offering building blocks to data-driven insights. Tools like MS PowerApps, AppSheet, and Airtable allow users to build apps without coding, enhance productivity, and enable rapid prototyping. BI tools such as Tableau, Power BI, and Qlik Sense also benefit non-technical users as they simplify data visualization while enabling teams to create dashboards and gain insights through intuitive interfaces instead of individual manual processes. Additionally, collaboration and data sharing platforms such as Google Data Studio or MS SharePoint enhance teamwork and the seamless distribution of data, further supporting a collaborative and data-driven work environment with everyone being able to be on the same page.

Make Upskilling a Priority

The effective deployment of data tools is crucial for unlocking the full potential of an organization. Investing in these tools not only supports upskilling efforts but also enhances data-driven decision-making, driving overall organizational strength. As companies navigate this transformation, several key considerations must be addressed to maximize the benefits of their data tools.

Ease-of-use for every employee is essential; selecting tools with intuitive interfaces and robust support systems ensures that they are accessible to all knowledge level employees, not just technical ones. Integration capabilities are also important, as tools should seamlessly connect with existing systems to create a cohesive data workflow.

Equally as important is a comprehensive training and support program to facilitate continuous learning and skill development. Lastly, scalability should be a primary consideration to ensure that the tools can grow alongside the organization and adapt to evolving data needs. By addressing these considerations, organizations can better upskill the power of data tools to drive growth and efficiency.

The effective use of data tools give companies a competitive advantage. It’s crucial now for every organization to invest in proper data tools to support upskilling and data-driven decision making across all technical and non technical employees. Organizations need to be able to stay up to date and on track with the fast paced technical changes in their industry, because without investing in upskilling data tools, organizations and team members will be put at risk of being left behind.

About the author: Arianna Vogel is a Senior Director of Product Marketing at Foursquare. In her role, she leads the go-to-market efforts for all of Foursquare’s suite of location-based solutions. Arianna first joined Foursquare via their merger with Factual where she joined over 6 years ago as a Product Marketing Manager. Prior to joining Foursquare, she worked as a Product Marketer in the social video space helping creators maximize the growth of their online audiences at technology platforms Epoxy and Vemba.

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