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Why These Three Data Management Platforms Stand Out – ReadWrite

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Deanna Ritchie


The tremendous inherent value of data has received a lot of attention in recent years. Unfortunately, in the past, companies have often ignored the importance of the data information they gathered.

Even if they gathered customer info, they often did little it. The information sat in piles of dark data that remained unanalyzed and unattended on forgotten hard drives or cloud-based storage sites. At other times businesses did make an effort but used incorrect data in the process. In fact, in 2016, a report claimed that bad data was costing the U.S. a staggering $3.1 trillion per year.

Struggles like these have led to a rise in the number of data management platforms (DMPs) available. Each tool offers to perform a similar set of items: to identify, collect, organize, and analyze data throughout an organization’s activities. Analysts can then distill this varying information into meaningful statistics and actionable recommendations.

Why These Three Data Management Platforms Stand Out

With so many data management platforms available, it can be difficult to decipher which ones have an edge. With that in mind, here are three of the best DMPs available, as well as the unique selling points (USPs) that help each one stand out from the crowd.

1. Acceldata

Acceldata is a growing DMP that focuses on data observability. The platform uses AI/ML to manage all data layers involved—the infrastructure layer, the data layer, and the data pipeline layer. According to its website, data pipelines are like modern supply chains for digital information.

For Acceldata, the primary goal is to keep a company’s data supply chain optimized and reliable. Its data observability platform identifies potential errors in order to fix any potential issues before they arise. This helps to keep things running like a well-oiled machine. At a glance, the platform is able to offer a comprehensive, cross-section view of a business’s data regardless of the form, source, technology, or scale of the incoming information.

The need for data reliability is important, and it is a benefit trumpeted by other tools as well. For instance, fellow DMP Monte Carlo heavily focuses on the reliability aspect of its data management tool. But Acceldata goes further by ensuring that its data isn’t just reliable but also understandable.

In other words, humans can use the program in an understandable manner to reduce risk and increase the speed of execution. This enables a company’s data strategy to keep in lock-step with the organization’s larger activities and goals.

2. Unravel

For up-and-coming DMP platform Unravel, simplicity is key. The data management company’s tool works like most DMP software. It can track, analyze, and maintain data across an organization’s various APIs and touchpoints.

However, Unravel takes things further by making them as simple as possible. The software takes the intensely complex elements of a modern tech stack and reduces it to an optimized and easy-to-understand level.

Unravel emphasizes factors like comprehensive analysis and full-stack visibility. The company also provides specific insights that pertain to each of its customer’s circumstances. It also provides AI-powered recommendations for how to address each issue.

In essence, Unravel’s goal is to take customers by the hand and walk them through the data observability process from start to finish. While some of this process is left in the hands of AI, it doesn’t change the fact that simple, easy-to-understand results are key.

3. Pepperdata

Pepperdata is another data management platform that takes observability seriously. The brand strives to create enhanced visibility and offer operational insights and recommendations for solutions.

Along with these common data observability activities, Pepperdata uses machine learning automation. The ML aspects of the software follow the sequential aspects of a problem, tracing it step by step through your system.

Given time, this doesn’t just help you identify and resolve issues. It can also help you understand how your system works on the back end.

Every user may not need this information, but the ability to deepen their knowledge and understanding can be a huge selling point for many customers. This is particularly true for those who feel overwhelmed by the ephemeral nature of a modern technological work environment.

There are countless data management platforms already in existence, with more being created every day. However, simply using a DMP isn’t a dependable solution. Instead, it’s important to look for the specific traits that help each platform stand out.

Data observability creates a more seamless, dependable, and comprehensible experience. Additional factors like reliability, simplicity, and added insights can make or break your DMP adventures, as well.

So consider what kind of tool you’re looking for. What will benefit your business the best? Once you’ve isolated that X factor, you can look for that capability in the DMP platform that you choose.

This ensures that you won’t just be collecting and analyzing data the right way. You’ll be able to creatively use it to your advantage, as well.

Image Credit: nataliya vaikevich; pexels; thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

Politics

Fintech Kennek raises $12.5M seed round to digitize lending

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Google eyed for $2 billion Anthropic deal after major Amazon play


London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 tech.eu report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from Kennek.io; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs

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Deanna Ritchie


As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations

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Deanna Ritchie


As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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