Role of An Analyst in 2023

Hoshang Mehta
October 4, 2023


Analytics has become a key element for decision making for businesses in the current world. But the role of an analyst has been changing with the advancements in technology and data being the focus of every decision. In this blog, we speak to modern analytics teams to understand how the role of an analyst is evolving and the emerging need of the data solutions to help teams move from insights to taking action.

As we speak to modern analytics teams, we are observing a pattern in how the role of an analyst is evolving where data is at the centre of every decision.

Challenges & Technological Advancements

The definition of an analyst is under ‘identity crisis’. Traditionally, analysts were regarded as the ones who can use their technical wizardry to query, wrangle, clean large chunks of data and then being able to convert raw data into visualizations via dashboards for business stakeholders to consume.

As data took the centre stage in the previous decade, we found that the expectation to ‘being data-driven’ had started to become a pre-requisite in several business facing roles as well.

Although the dashboarding solutions were being designed for ‘self-service’, many deployments of these solutions ended up being “report factories” offering only a single-player environment where the semantic layer was used by technical experts to create reports for others. This often reintroduced the bottlenecks and frustrations that self-service BI was supposed to get rid of.

With the emergence of more advanced code abstraction layers (ofcourse, ChatGPT and NLP)- teams will directly go from 'describe to action'.

Eventually non-data teams would be able to operate on data themselves more effectively AND finally the role of an analyst will be respected more as 'advisors' of data rather than 'report factories' for ad hoc reporting. Hence, an emerging need within data solutions to have the ability to explain insights, direct a narrative, create and close analytical feedback loops and eventually helping reach from insights to decisions quickly and together will become inevitable.

Collaboration & Modern Solutions

Having previously lived the life of a frustrated analyst, I relate strongly to this problem.

In our interviews with data teams, we've found that an average data practitioner hops between at least 4 unique tools to query, explore data and 5 communication channels to gather requirements, explain insights, work on follow-ups and present data which almost always gets lost in transit.

In our recent conversation with Dhruv Kadakia who is a Senior Data Analyst at JioSaavn we spoke about how the role of an analyst is not only pertaining to be able to query data but is evolving more towards understanding what the insights mean in business context.

Speaking more about the analytical workflow, analysts today are skilled at querying data from various sources using SQL, R or Python but eventually all of the gathered data is communicated to larger business stakeholders via disparate excel sheets and the actual knowledge sharing over data happens over multiple communication channels (messaging apps, meetings, emails).

Conversations around data where the actual knowledge lies all exist within different channels so - what we learn from data, context around numbers and the thought process behind making a particular decision is difficult to retrieve or refer today. There is an opportunity for modern data solutions to make collaboration the centre of everything data related so that teams can move towards decision-making faster.

Today, with more focussed managed services for ETL/ELT and reverse ETL existing in the Modern Data Stack, there may be an exciting opportunity to help teams move from insights to actually taking action from one collaborative interface.


In conclusion, the role of an analyst is evolving to be more data-driven and focussed on understanding the business context. Today, with the emergence of more advanced code abstraction layers, teams are able to move from insights to taking action quickly and collaboratively. As data becomes the focus of every decision, it is important for analysts to be able to understand the business context for the data, communicate their insights effectively and collaborate with stakeholders to take action.


What is the traditional role of an analyst?
How has the role of an analyst changed over the past decade?
What are the limitations of modern dashboarding solutions?
What challenges do data practitioners face in current workflows?
What did Dhruv Kadakia from JioSaavn mention about the evolving role of analysts?
Why is collaboration becoming central to modern data solutions?
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