Data Activation An introduction by Peliqan

Understanding Data Activation

In the fast-evolving realm of data-driven decision-making, data activation stands as a pivotal strategy that allows companies to transform raw information into actionable insights. At Peliqan, we’re on a mission to redefine data activation, making it accessible and impactful for users across diverse scenarios, regardless of their technical background or support from a data engineering team.

The Modern data stack

The modern data stack is a contemporary approach to managing and leveraging data within an organization, comprising a set of integrated tools and platforms designed to handle the end-to-end data lifecycle. Typically, it includes at least four key components:

  • Data Acquisition: Where data is generated, collected, or ingested from various sources such as events, SaaS tools and internal databases.
  • Data Integration: The process of consolidating data into a centralized view, often involving a data warehouse to facilitate a unified and holistic understanding of the data.
  • Data Transformation: The phase where data is cleaned, prepared, and transformed into a usable state, commonly performed within the data warehouse.
  • Analytics: The location where data is analyzed and consumed, often facilitated by Business Intelligence (BI) tools, enabling organizations to derive meaningful insights.

For the majority of organizations, that’s where the Modern data stack stops today, at the Analytical layer with BI tools as the final destination of the data. However, while analytics and BI provides insights, it does not trigger actions. That’s where Data Activation comes in.

Defining Data Activation

The modern data stack serves as the foundation for effective data activation. Data activation, as a strategy, operates within this stack, focusing on the last and final piece of the cycle — making data actionable for business users. While the data stack helps collect, integrate, and analyze data,

Typical Data activation implementations focus on customer-centric, marketing, and sales use cases. They enable for example the seamless “write back” of customer information into the operational systems utilized by marketing teams, customer success professionals, and sales teams. Commonly used terminologies in this domain include CDP (Customer Data Platform) and Reverse ETL, serving as pivotal mechanisms to achieve effective data activation.

However Data Activation also comes in many other forms including proactive alerting, data synchronizations, data enrichment, predictions etc. and is highly relevant for any department within an organization.

Challenges on Data Activation

Data Activation relies heavily on data engineering teams

Today there’s a big dependency of data engineering teams gathering and providing the right data to the teams levering or building the data activation use cases.

Data activation typically starts from a data warehouse or data lake – built by a fully-equipped data team.

How can you activate your data when you don’t have a fully built out data warehouse? What if your company’s data warehouse lacks crucial data for your activation flow, such as domain-specific information from a newly introduced marketing tool or ‘small data’ like an Excel spreadsheet containing budget targets?

Many Data Activation processes run as a black box

Measuring the outcome of the data activation process is crucial. Instead of merely examining logs to track events, we advocate assessing the results and comparing them with the source data. This approach allows you to determine if the desired outcomes have been achieved.

Will LLMs replace data engineers?

Ultimately, we must consider the integration of AI, ML, and LLMs. We foresee a transition from traditional data synchronization to more intelligent data management methods. The role of AI and ML is evolving beyond mere data replication towards dynamic decision-making. An initial step involves AI assisting in transforming you into a low-code data engineer — simply instruct ChatGPT and it will write the query for your Customer 360° view.

Looking ahead, LLMs, fueled by your data, could potentially take over the role of a data engineer, eliminating the need for explicit instructions on how to combine data for actionable insights.

Peliqan's Commitment to hassle-free Data Activation

We believe that data activation should be user-friendly, avoiding the need for extensive data engineering. Peliqan delivers true data activation for all users.

Data activation is the key strategy for companies to become data driven. It’s about getting the right information to the right person at the right time, or even better, do the right thing at the right time – manual or automated.

Peliqan simplifies data activation. Start from your data sources, effortlessly connect and combine company and your own data. Take control of the end-to-end process with ease. Peliqan makes data activation accessible for all. Contact us for more information.



Piet-Michiel Rappelet is a founder of Peliqan. Before Peliqan, Piet-Michiel co-founded, a no-code iPaaS integration platform. was acquired by Qlik in 2020 and Piet-Michiel became Director of Product Management Foundational Services at Qlik. Piet-Michiel’s primary interest is in scaling SaaS software and rolling out customer-oriented service teams. Piet-Michiel holds a Masters degree in mathematics, he lives with his wife and two kids in Belgium.