Sep 26, 2022
“Delve into the world of Explainable AI (XAI) and its evolving definitions. Discover how XAI techniques are being applied in healthcare and finance, with explanations taking various forms, from human-language to heat-map interpretations.”
“Learn how explainability aids developers and machine learning practitioners in clarifying AI system decision-making processes. Understand its role in bridging the gap between technical and non-technical audiences.”
“Despite the demand for explainability, challenges persist in defining key terms and providing guidance on selecting and testing explanations. Explore the debate over whether opaque models should be replaced with interpretable ones.”
Sep 19, 2022
The prevalence of CDO roles has grown globally in many sectors. To be effective, a CDO must be focused on business value, balance enablement and control, and view data and analytics as a value chain instead of a centralized, isolated silo. Read on in this CEOWorld Magazine article to learn more about the future of the CDO role.
Global data creation is expected to reach 175 zettabytes by 2025, and the global big data and analytics market is on pace to reach $135.71 billion. Companies worldwide are scrambling to reengineer their data strategy. The CDO role is one of the newest potential additions to an organization’s senior leadership team, and comprises seven critical job types. The CDO role may differ from one business to another, depending on the market context. To remain competitive, organizations will need to transform their data systems. CDOs are crucial to this process
“Data is the lifeblood of an organization, but many businesses aren’t investing enough in deriving true value from it. This is why the Chief Data Officer (CDO) role has become so popular in recent times. This article from Intelligent CXO lists five reasons why CDOs are the leaders of the future. A CDO is a trained data strategist that can interpret data and make the best use of it. He or she helps to make data less scary and more open and ensures that every employee understands the value of data-driven strategies.
The initial incarnation of the chief data officer (CDO) was more of a governance job than an analytics-focused one. This Forbes article explains how the CDO role is starting to split into several different functions. In the beginning, there was a lot of talk about being data-driven, but as these data stores expanded and evolved, companies recognized that they were not just assets but liabilities, and started to organize and make data actionable. With the shift from focusing on governance to focusing on analytics, it’s important to rethink data architecture.
Sep 12, 2022
For businesses, the race towards accelerating innovation is (or should be) the highest priority. In this article, TechCrunch outlines the benefits and challenges of adopting cloud. Public cloud technology allows businesses to quickly test out new technologies, scale up or down as needed, and retain data in a specific geographical region for privacy and regulatory compliance.
Recently, unexpected events have exposed significant structural weaknesses, which are amplified by global trade disputes, environmental disasters, and civil unrest. This EY article explains how cloud technology can enable organizations to transform quickly and reframe their future. Businesses should prioritize speed and resilience over cost optimization and monitor data in real-time to pre-empt adverse outcomes and gain significant competitive advantages.
The future of cloud appears to demand a new approach that considers business, technical, and financial priorities together to gain greater value from cloud innovation strategies. Read on to explore four potential scenarios for the future of cloud innovation strategy in this article by Deloitte. Cloud technology can help organizations innovate across today’s enabling, tomorrow’s disruptive, and future next-horizon technologies. The CIO should guide organizations in their use of cloud technology to innovate and help them understand the business, technical, and risk sides of the innovation equation.
Aug 29, 2022
A lack of professional development is one of the top reasons for employee turnover. Businesses cannot afford to wait and allow other, more data-forward enterprises to win top talent. This Forbes article explains why data literacy education is crucial for success. The modern workplace is rapidly changing, and data plays a central role in many of those changes. However, despite these changes, only 21% of employees believe their employer is preparing them for a more data-oriented and automated workplace.
Today, companies are amassing more data than ever before, and also undergoing a digital transformation to become more data-driven. Given the changes in the data and analytics landscape, non-data professionals need to become data literate. Read on in this article from Eliiza to learn more about how both business and employees can benefit from improving data literacy across the workforce. Businesses are adopting a data mesh architecture where data and analytics functions are delegated to individual business domains.
A data-driven culture is an organizational mindset that uses data to inform business decisions, predict customer behavior and drive transformative technologies. To create a data-driven culture, follow these 10 steps in this article from Hexacta. The key to making complex data work for a solution-oriented management system is asking the correct questions and knowing how to solve problems. Root Cause Analysis can help identify business problems and priorities early on.
Aug 22, 2022
Data is valuable only if it can be translated into insights, and organizations are still struggling to see insights clearly through their data. In this article, Treehouse Technology Group outlines the steps you can take to derive actionable insights from your data. To turn data into useful information, you need to put context to the data and establish why the data is important. You also need to anticipate the outcome of the project and elaborate on how the results will be used or integrated into the business.
Top-performing companies use data to make decisions about their business, and these companies gain a strategic advantage over their rivals. This blog from Sisense Team aims to help you improve your decision-making process. Data-driven companies are more customer-focused, enjoy deeper insights into the customer and their journey, and are more agile and better able to respond to markets.
Due to the recent advancements in modern technology, data-driven decision making is starting to be employed across various industries. This article from Softjourn explores the ways various companies are benefiting from data-driven decisions. Data-driven decision making (DDDM) uses past information to predict what will happen in the future. KPIs are used to measure the performance of systems and to see how close they are to achieving business goals.
Aug 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.
Aug 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.
Aug 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.
Jul 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.
Jul 18, 2022
Welcome to another edition of Executive Data Bytes! This week, we are discussing some interesting data science roles and their responsibilities.
