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New Survey Indicates Use of Alternative Data in Investment Community Shows No Signs of Slowing

Lowenstein Sandler announced the release of Alternative Data: The New Oil for the Digital Economy? The 2022 Lowenstein Sandler Alternative Data Report. The survey, which is the third annual survey on this market development from the firm’s Investment Management Group, finds demand increasing for alternative data—not only driven by hedge funds, but also by private equity firms and venture capital investors. Alternative data is generally defined as information not contained in company filings, press releases, analyst reports, or other traditional information sources.

Hypothesis-led data exploration is failing you …

In this special guest feature, Aakash Indurkhya, Co-Head of AI at Virtualitics, suggests that you should set your assumptions aside and start looking at your data through the lens of AI. Cut through the noise, surface significant insight, and take aim at the real issues. Forget data as oil–data is gold and Intelligent Exploration is the sophisticated tool that’s going to help you get at it.

“Above the Trend Line” – Your Industry Rumor Central for 12/8/2022

Above the Trend Line: your industry rumor central is a recurring feature of insideBIGDATA. In this column, we present a variety of short time-critical news items grouped by category such as M&A activity, people movements, funding news, financial results, industry alignments, customer wins, rumors and general scuttlebutt floating around the big data, data science and machine learning industries including behind-the-scenes anecdotes and curious buzz.

How to Ensure an Effective Data Pipeline Process

In this contributed article, Rajkumar Sen, Founder and CTO at Arcion, discusses how the business data in a modern enterprise is spread across various platforms and formats. Data could belong to an operational database, cloud warehouses, data lakes and lakehouses, or even external public sources. Data pipelines connecting this variety of sources need to establish some best practices so that the data consumers get high-quality data delivered to where the data apps are being built.

Report: Audit Industry Rising to the Data Analytics Challenge

With businesses facing the strongest economic headwinds in years, the Chartered Institute of Internal Auditors (Chartered IIA) is urging internal auditors to embrace data analytics to navigate more risky, uncertain, and volatile times ahead. The new report, “Embracing data analytics: Ensuring internal audit’s relevance in a data-led world,” from Chartered IIA in partnership with AuditBoard aims to encourage internal audit to fully embrace data analytics and support the organization in doing the same.

2023 Trends in Data Governance 

In this contributed article, editorial consultant Jelani Harper offers his perspectives around 2023 trends for data governance. The valuation of data governance, both to the enterprise and to data management as a whole, is evinced in two of the most discernable trends to shape this discipline in 2023.

How AI Enables Organizations to Move from Network Monitoring to Proactive Observability

In this special guest feature, Stephen Amstutz, Head of Strategy and Innovation, Xalient, discusses the role of AI in the shift from network monitoring to observability, highlighting the benefits of AI observability in limiting downtime, protecting brand reputation, and ultimately saving money!

What to Avoid When Solving Multilabel Classification Problems

In this contributed article, April Miller, a senior IT and cybersecurity writer for ReHack Magazine, suggests that If you are working with a model with a multilabel classification problem, there is a likely chance you will run into something in need of fixing. Here are a few common issues you may encounter and what to avoid when solving them.

Research Highlights: R&R: Metric-guided Adversarial Sentence Generation

Large language models are a hot topic in AI research right now. But there’s a hotter, more significant problem looming: we might run out of data to train them on … as early as 2026. Kalyan Veeramachaneni and the team at MIT Data-to-AI Lab may have found the solution: in their new paper on Rewrite and Rollback (“R&R: Metric-Guided Adversarial Sentence Generation”), an R&R framework can tweak and turn low-quality (from sources like Twitter and 4Chan) into high-quality data (texts from sources like Wikipedia and industry websites) by rewriting meaningful sentences and thereby adding to the amount of the right type of data to test and train language models on.

Inside Bigger, Faster, Greener Storage for Enterprises

In this sponsored post, Eric Herzog, CMO, Infinidat, believes it is possible to apply the B.F.G. equation to an enterprise or service provider / hosting infrastructure without compromising any one of the factors – bigger, faster or greener – for the sake of the others.