Streamlining the BI Pipeline with AI-driven Data Preparation

The goal is to turn data into information, and information into insight. - Carly Fiorina

It is common knowledge that in today’s data-driven world, it is Business Intelligence (BI) that plays a significant role in helping organizations move ahead with better-informed decisions. But BI does not function on its own. It relies heavily on data. The quality and accessibility of data are therefore highly critical. In the pursuit of accurate and meaningful data for deep insights and strategic planning, AI-driven data preparation has emerged as a game changer. Raw data is therefore transformed into intelligence by meticulously designed pipelines that seamlessly gather, cleanse, analyze, and interpret information, ultimately empowering informed decision-making and insightful discoveries. Let’s see how. 

The global data integration market evaluated at USD 12.14 billion in 2022 is expected to hit around USD 39.25 billion by 2032, growing at a CAGR of 12.5% from 2023 to 2032. 

Data is the heartbeat of modern businesses driving innovation, decision-making, and progress. It is the harnessing of data that is the key to growth and success. Data is prepared by gathering, processing, profiling, structuring and transforming information so it can be used in business intelligence (BI), analytics and data visualization applications. 

Business Intelligence has been helping make informed decisions and empowering stakeholders at every level of an organization to access and understand crucial information. Adding AI to data preparation has made the quantum leap that has revolutionized the industry by helping businesses surge dramatically ahead. 

The Pitfalls of Manual Data Preparation in a Data-Driven World

Interestingly, with traditional manual data preparation, data scientists spend around 80% of their time on data preparation and 76% of data scientists view data preparation as the least enjoyable part of their work. 

In 2009, data scientist Mike Driscoll described “data munging (suffering),” as the “painful process of cleaning, parsing, and proofing one’s data” which is one of the three sexy skills of data geeks. In 2013, Josh Wills, Director of Data Engineering at Slack told Technology Review “I’m a data janitor.” 

To attract the much-in-demand but hard-to-find data scientists, the next step (as predicted by Forrester too, in 2016) was to replace manual data preparation with automation. Today, AI-driven data preparation also leaves data scientists free to focus on the more challenging and enjoyable part of their job. 

To realize the importance of AI-driven data preparation, let’s understand some of the major challenges of manual data preparation and how automation takes care of these challenges. 

Labor Intensive 

The traditional manual data preparation process is labor intensive at every step from data collection, to data cleaning, to data transformation to finally make it ready for analysis. 

Prone to Errors

Manual handling of data always leaves room for human errors which could lead to inaccurate results and analysis. 

Scalability Challenges

As the volume of data increases exponentially, manual data preparation becomes increasingly impractical and impossible in terms of time, cost, efficiency and accuracy.

Limited Scope of Reproduction

Manual data preparation processes cannot be reproduced easily as it is difficult to ensure consistency in the steps taken by different team members for different iterations.

High Costs

There is a high cost associated with employing skilled professionals to perform manual data preparation, whose time can be better utilized for performing higher-level tasks.

Meeting these challenges necessitates the implementation of automated tools and processes to streamline data preparation. Automation rules out the likelihood of errors and enhances overall efficiency. It handles huge data volumes swiftly and efficiently, ensuring uniformity and replicability. In a nutshell, automation empowers businesses to unlock the complete potential of their data, ultimately leading to sharper decision-making and a step ahead of the competition. It is an indispensable tool for businesses aiming not just to thrive, but to excel.

The AI Advantage in Data Preparation for Your BI Pipeline

When we are talking about AI-driven data preparation, we are looking at a great range of groundbreaking merits that substantially enhance the productivity and proficiency of data handling and analysis and empower organizations to make more informed and impactful decisions. Here's how AI revolutionizes the BI Pipeline -

• Efficiency & Speed: With AI at the helm of data preparation, labor-intensive activities like data cleaning, sorting, and transformation are streamlined through automation, significantly reducing the overall processing time. Tasks that used to demand weeks or even months of manual effort can now be accomplished in a mere fraction of that duration. This also allows adept BI professionals to channel their expertise toward more advanced analytical tasks.

• Enhanced Data Quality: AI algorithms demonstrate exceptional proficiency in detecting and rectifying errors, redundancies, and incongruities within datasets. Through the utilization of machine learning models, data preparation tools possess the capability to independently cleanse data. This leads to datasets of superior quality and reliability for BI analysis. Enhanced data integrity also generates more precise and dependable insights, supporting informed decision-making.

• Pattern Recognition & Anomaly Detection: AI has the capability to discern patterns within datasets and also predict missing values or identify anomalies. It can augment datasets by adding supplementary information from external sources, such as demographics, weather data, or market trends, elevating the depth of analysis. This empowers BI analysts to identify meaningful trends and outliers, which might have been missed with manual approaches.

• Semantic Understanding: Data preparation tools enhanced by AI have the capacity to understand the significance and context of data. This enables a more precise classification, labeling, and conversion of information. As an example, they can distinguish between product names and product categories, leading to more accurate analysis and reporting.

• Seamless Data Integration & Transformation: AI-driven data preparation tools can effortlessly integrate data from a wide range of sources, be it structured or unstructured. Since they can make sense of intricate relationships within data, they can automatically perform complex transformations, including tasks like recognizing dates, performing aggregations, and creating calculated fields, all without the need for human intervention. 

• Scalability for Big Data: As enterprises grapple with ever-expanding volumes of data, scalability emerges as a critical concern. Data preparation tools powered by AI are meticulously designed to seamlessly manage extensive datasets, ensuring that data processing retains its efficiency and accuracy, even amidst escalating data scales.

• Consistency & Reproducibility: Through automated processes, a uniform and consistent application of steps across all data is ensured, eliminating discrepancies that may arise from manual intervention This results in enhanced data quality and reliability. Moreover, it enables easy replication of outcomes, thereby simplifying auditing procedures and reinforcing compliance with regulatory standards.

• Data Governance & Compliance: Data preparation tools powered by AI act as vigilant overseers of data governance protocols. They can automatically detect and highlight sensitive information, and guarantee compliance with regulations such as GDPR, HIPAA, and various others.

The Biggest Success Story with AI-Enhanced Data Preparation

Netflix, the global streaming giant, is a prime example of a company that leverages AI-driven data to drive its business decisions. To illustrate further - let’s say, you sit down to watch a horror movie on Netflix and as it gets scarier you can't take it any longer and stop it. After that, you are recommended light-hearted films, unlike the one you stopped halfway through.

How does Netflix do that? Netflix has over 238.39 million paid subscribers worldwide and the data Netflix collects is mind-boggling. Using advanced data and analytics, Netflix creates a series of algorithms that personalize content according to viewers’ preferences. The algorithm predicts what you are likely to watch next and arranges selections into rows based on your viewing preferences. Not surprisingly, 80% of the content streamed on Netflix is based on its recommendation system. 

This is a classic case where AI-driven data preparation has helped streamline the BI pipeline and propelled Netflix to the top, to become the market leader it is today. 

5 Quick Tips for Selecting AI-driven Data Preparation Tools

1. Consider the level of maturity and sophistication of data preparation tool’s underlying AI models to ensure to ensure it can effectively handle complex data processing tasks..
2. Prioritize tools that are scalable to take care of booming data volumes and evolving business requirements.
3. Look for solutions with a proven track record and positive customer reviews.
4. Opt for a tool that provides flexibility in terms of data source compatibility, to ensure seamless integration with your current infrastructure.
5. Choose vendors with a robust support and training ecosystem, as ongoing assistance is crucial for successful implementation.

Conclusion

Incorporating AI-powered data preparation into your BI pipeline will transform your approach to data handling and analysis, providing you with more accurate and dependable insights for well-informed decision-making. By selecting and integrating the appropriate tools, you can unleash the complete potential of your data leading to phenomenal business achievements. The integration of AI-driven data preparation represents a significant stride in optimizing the BI pipeline, streamlining processes, and paving the way for sharper and more strategic decision-making. This technology isn't merely progress; it's a giant leap toward a more dynamic and competitive future.

How AirQuery can help you? 

At AirQuery, we offer the most comprehensive AI-driven Data Preparation tool to streamline your BI Pipeline. If you are seeking to rise above the competition, check us out and tick every box of BI requirements you have. Because success awaits those who are ready to take the leap. 

Request a demo to find out more: https://info.airquery.com/get-started-v2