The Evolving Role of the Business Analyst

The role of a business analyst comes in different forms and can even span across different job positions. At the same time, new types of data, tools, and technologies are shaping the jobs of analysts, taking them in exciting new directions.

The role of a business analyst comes in different forms and can even span across different job positions. At the same time, new types of data, tools, and technologies are shaping the jobs of analysts, taking them in exciting new directions.

While the specific tasks and responsibilities of someone with the title “Data Analyst,” “Business Intelligence Analyst,” or “Business Analyst” may vary to an extent, and sometimes even between two people with the same title, the core of an analyst’s mission remains the same: generate insights for an organization, generally with a big dose of data as a starting point.

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The Rise of the Citizen Data Scientist

AI maturity cannot improve without expanding the breadth of people that have access to and work with data on a day-to-day basis. This means that data scientists can’t be the only people in an organization extracting value from data.

While automated machine learning, or AutoML, is useful for embedding AI methodology at the core of an organization, it is only truly impactful when a variety of teams can explore the results. Thus, from this cultural shift toward a data-driven culture and the economic imperative of data insights, the citizen data scientist is born.

 

Regardless of their actual title (marketing analytics manager, risk analyst, etc.), this role is a potential win for all analysts, who can strengthen insights with more valuable and less mundane work. 

While it’s true that incorporating the work of non-data scientists into data projects in meaningful ways requires a fundamental shift in mindset around data tooling, analysts don’t need to master all the intricacies of advanced machine learning, feature engineering, etc. What they do bring to the table is an intimate knowledge of the problems at hand and the business questions that need to be answered.

Dataiku Is for Analysts

Dataiku is the platform democratizing access to data and enabling enterprises to build their own path to AI.  By making AI accessible to a wider population within the enterprise, facilitating and accelerating the design of machine learning models, and by providing a centralized, controlled, and governable environment, Dataiku allows businesses to massively scale AI efforts.

 

Analysts, no matter their level of technical expertise, can reap the benefits of data science without advanced coding, engineering, or extensive training by leveraging visual AutoML and other visual tools. Dataiku covers the entirety of the data pipeline, making data science and machine learning an extension to analysts’ current capabilities and skillsets.

From Excel to Dataiku

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Data Access: With Dataiku, analysts can easily connect to and start exploring any and all types and sizes of data – from Excel to Hadoop – no matter where it is stored.

Data Preparation: Analysts can increase productivity and shorten the time to value on projects with interactive and visual data cleaning, enrichment, and transformations.

Data Exploration: Without relying on either advanced training or coding, quickly discover trends and patterns in large datasets and create accessible visual reports to communicate findings to teams at large.

Auto ML: Use AutoML & AI features to quickly uncover or predict patterns in large datasets without needing to dive deep into the intricate math and coding constituents of data science and machine learning.

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