#62: Low-code data science platforms: 3 things CIOs should know💻
#62: Low-code data science platforms: 3 things CIOs should know💻
Hello,
This newsletter will take you about 4 minutes to read.
I. Spotlight: Low-code data science platforms: 3 things CIOs should know💻
Organizations across industries are turning to data and analytics to solve business challenges. A survey by New Vantage Partners found that 91 percent of enterprises have invested in AI. However, the same study found that just 26 percent of these firms have AI in widespread production.
Organizations are struggling to solve business challenges with AI. They find that building machine learning (ML) applications takes time and requires expensive maintenance and talent that’s in short supply. Leaders say that over 70% of data science projects report minimal or zero business impact.
Here’s how low-code ML platforms can help tackle these challenges.
Low-code is a software development approach that leverages a visual user interface to create applications instead of traditional hand-coding. For decades, developers built applications by writing thousands of lines of code from scratch, often round-the-clock.
Building software solutions using low-code falls somewhere in the continuum between programming from scratch and buying off-the-shelf. It brings the best of both worlds by balancing flexibility and time-to-market.
A low-code development platform (LCDP) is considered quicker to build, economical to maintain, and developer-friendly because of its visual approach.
Low-code tools empower enterprises by democratizing software development. Today, anyone with a business interest and basic technology skills can build an app using low-code technology. According to Gartner, by 2024, more than 65 percent of all app development will be on low code. Globally, the low-code market is projected to reach $187 billion by 2030.
II. Industry Roundup:
1. Article: How to Train Generative AI Using Your Company’s Data
13 minutes | Â HBR| Tom Davenport and Maryam Alavi
Generative AI, leveraging OpenAI's large language models, is transforming how companies manage and distribute knowledge. Adopted by industry giants like Google, Bloomberg, Morgan Stanley, and Morningstar, it's allowing users to pull information from massive databases using natural language. Yet, striking a balance between customizing AI models with high-quality content and maintaining data privacy and accuracy demands continuous evaluation, legal oversight, and targeted training.
->Â Read the Article
2. Article: The rewired enterprise: How five companies built to outcompete
13 minutes | McKinsey Digital | Santiago Comella-Dorda, Julie Goran, Kent Gryskiewicz, Eric Lamarre, and Noor Narula
Digital transformation requires reimagining enterprise operations as interconnected platforms rather than isolated silos. Emphasis shifts to distributed engineering, using microservices and cloud technologies. Data analytics become embedded organization-wide, not centralized. The crux is a culture shift towards continuous learning, stringent performance tracking, and code reusability. This holistic approach to digital reinvention underpins a successful, rewired enterprise.
->Â Read the Article
III. From my Desk:Â
1. Recognition: LinkedIn Top Voice in Decision-Making!
1 min | LinkedIn
Happy to share that I've been recognized as a LinkedIn Top Voice in Decision-Making! Helping organizations make better decisions with data & analytics has been my priority for over a decade. My work aims to empower leaders to orchestrate org-wide Decision Intelligence, build teams to deliver AI-driven solutions and realize business ROI from data. I'm profoundly grateful to LinkedIn for this recognition and even more so to all of you who have engaged in fruitful dialogues and discussions.
->Â Read the Post
2. Announcement: Contributions to LinkedIn collaborative articles
9 mins | LinkedIn
Exciting news! I've recently begun contributing to collaborative articles on LinkedIn. These pieces are a melting pot of insights and perspectives from diverse industry leaders, providing a comprehensive understanding of various business trends. One of my recent contributions delves into the nuances of explaining AI to diverse audiences. You can check it out at the link below - I believe you'll find the content both enlightening and thought-provoking.
->Â Read the Article
Thank you for subscribing and reading the newsletter. I appreciate your attention.
Ganes.
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I’m Ganes Kesari. I publish ‘Data-Driven Future’ to help understand how data shapes our world, explore key trends, and explain what they mean for you today. I speak and write to demystify data science for decision-makers and organizations.
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