Executive Bytes

08.15.2022 Executive Data Bytes – Data Fabric: What it is, Why it is, And Do You Need It

August 15, 2022

A data fabric is an architecture and set of data services that provide consistent capabilities across a choice of endpoints spanning hybrid multi-cloud environments. It enables a unified data management architecture so that enterprises can gain from an extensible and converged data capability. This article from Spiceworks outlines what you really need to know about data fabric. While we live in a data-driven age, organizations spend a disproportionate amount of time on routine tasks and not enough on value addition. Data fabric rectifies this imbalance by removing back-end bottlenecks in data management.

Data management is prone to human errors. If data and analytics leaders want to reduce these errors, and overall costs, it’s crucial that they shift toward modern solutions like AI-enabled data integration. In this article, Gartner says the emerging design concept called ‘data fabric’ can be a robust solution to data management challenges. Data fabric works like a car’s autonomous element. It monitors the data pipelines as a passive observer at first, and then starts suggesting alternatives that are far more productive.

Data fabric architecture has emerged as a way to facilitate data exchange among the many disparate systems that support the business. However, like anything, data fabric architecture has pros and cons. This ITPro Today article explores some of these advantages and disadvantages. A data fabric is a technology infrastructure used to access and move data, and is often positioned as a disruptive, zero-sum architecture. However, data fabric is a complement to, not a replacement for, data management tools, practices and concepts.

08.08.2022 Executive Data Bytes – ‘Who’s ON First?’​ – Prioritizing your AI projects for success

August 8, 2022

Cloud storage and computation have enabled the efficient processing of huge data sets to draw critical insights using Artificial Intelligence (AI). However, with so many options, deciding where to devote your resources is the most difficult part. Learn more about how you can prioritize your AI projects in this article from The Enterprisers Project. Prioritization helps businesses achieve long-term success by taking all factors into consideration and making thoughtful decisions, rather than executing AI projects on an ad hoc basis.

Many businesses are considering how Artificial Intelligence (AI) and machine learning (ML) fit into their strategy. This article from Excella explores why your organization must decide on a set of needs and goals, and why it’s imperative to decide what level of accuracy is required and how timely insights need to be. AI/ML projects are challenging because they contain significant unknowns, require rapid exploration and fast feedback to learn and adjust, and involve uncertainty with the data, modeling algorithms, and the interactions of key variables.

Machine learning is a truly momentous time for the enterprise, with investments soaring and a growing number of use cases that can create tangible business value. However, many organizations are still struggling with important phases of the AI/ML lifecycle, including governance. In this article, TechBeacon explains the importance of Ai/ML governance. AI/ML governance is the overall process for how an organization controls access, implements policy, and tracks activity for machine learning models. It includes regulatory compliance and audit risk, but also forms the bedrock for minimizing risk while maximizing ROI.

08.01.22 Executive Data Bytes – How do you invest in AI and automation? And… is it for you?

August 1, 2022

Companies are spending serious money on artificial intelligence (AI) in 2022, and many are already making good money from the technology. One of the challenges with AI in recent years has been that projects involving the technology have frequently lacked sufficient economic returns. Read on in this MIT Sloan article to find out how companies are increasing their ROI. In the 2022 survey of senior data and technology executives by NewVantage Partners, 92% of large companies reported that they are achieving returns on their data and AI investments, and 26% have AI systems in widespread production

Artificial intelligence (AI) is one of the fastest-growing industries, and companies are investing in AI to automate and enhance business processes and generate more leads. Before you think about investing, read this article by Forbes to learn four steps you should take first. AI can solve many business problems, but it may not be the right solution for every business. Companies that lack enough data or continuous series of data flow may not be suited for AI automation

AI is a buzzword that gets more attention nowadays. AI can help your company in any number of ways, but you need to know exactly what you’re looking to achieve and how much it will cost. This Benchmark One blog answers the question, ‘How can AI help my business?’. There’s no single answer to how to incorporate AI into your small business. You can use virtual assistants, AI-run accounting, and market-research software, or pay for per-project AI services.

07.25.2022 Executive Data Bytes – This data, or that data – How to choose?

July 25, 2022

Many enterprises have mastered ‘small data,’ but big data is largely unstructured and random. Organizing big data is key to uncovering meaningful insights. This article from 3Pillar Global aims to teach you some best practices to get the most out of your data. Tableau reports that nearly 80% of employees are more likely to stay at a company that offers data-skilling programs. To help your team make sense of big data, implement these solutions.

The data analytics market is booming, and the demand for data analytics professionals is also exploding. This Forbes article presents the top eight trends that will define the data analytics market in 2022 and beyond. Composable data analytics allows organizations to combine and consume analytics capabilities from various data sources across the enterprise for more effective and intelligent decision-making.

Today’s business landscape runs on data. To make strategic decision-making, unearth new revenue streams, and reveal hidden waste generators, you need to assemble a tech stack that connects all relevant data sources. Read this article from 3Pillar Global to learn how to get the most out of your data. According to Harvard Business School, companies are better at collecting data about customers and competitors but fall short when it comes to analyzing insights and applying them strategically.

07.18.2022 Executive Data Bytes – Who does what? – Data Roles and Responsibilities

July 18, 2022

Welcome to another edition of Executive Data Bytes! This week, we are discussing some interesting data science roles and their responsibilities.

07.11.2022 Executive Data Bytes – There Is No Such Thing As A Crazy Idea

July 11, 2022

Welcome to another edition of Executive Data Bytes. This week, we are illustrating the point that there is no such thing as a crazy idea!
An idea is just a thought, a mental spark. It’s neither good nor bad until someone translates it into reality. Ultimately, it’s the context that proves whether an idea was good or not; even a ‘brilliant’ idea is worthless if it stays in someone’s head.