Tag: Data Management

Digital transformation benefits your small business or large organization by increasing productivity with scalability in IT infrastructure, expanding data storage and resources, and accelerating application delivery. However, the large-scale expansion of web services like cloud environments has created challenges for IT professionals and engineers, affecting their security and operational efficiency. To curb these challenges, here are some of the most effective solutions that will enhance your company’s use of artificial intelligence for IT operations (AIOps) by making complex automated decisions and managing large-scale data.

Use Cases for AIOps for Large-scale Data and Workload Management

AIOps can provide several benefits to your business to streamline and automate their IT operations and management processes. Here are a few use cases:

Detecting And Fixing Issues More Rapidly

AIOps offers full insight into the private, hybrid, and public cloud resources that identify and fix problems with large-scale data swiftly. AIOps platforms may combine this insight on the event and problem data to analyze the data to identify the issue before it arises.

How to Strengthen AIOps in Data Management

AIOps platforms are designed to handle large-scale data with the help of tools that offer various data collection methods and visual analytical intelligence. Here are a few strategies to strengthen AIOps in data management to handle the operations more effectively:

Define Goals and Objectives

Identifying the goals and objectives for implementation of AIOps helps your IT team identify the specific areas where IT operations are needed from AIOps technologies. The most important AIOps technologies that companies might need are performance optimization, capacity planning, and incident management.

Evaluate Data Sources and Infrastructure

Identifying relevant data sources can give better insights for AIOps, like metrics, log monitoring tools, events for evaluating existing infrastructure, and DevOps services that ensure data collection, processing, and storage requirements for AIOps.

Conclusion

AIOps is a big deal in the IT industry because it has the potential to transform your business, and it is no no-brainer to go with it. To make things easy to use, we have made a list of the best AIOps solutions that have features, tools, and use cases that will help you find the perfect platform for your business.

To Know More, Read Full Article @ https://ai-techpark.com/aiops-for-large-data/ 

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Artificial intelligence (AI) has revolutionized data management, empowering organizations to leverage data for informed decision-making.This article explores the transformative impact of AI in data management, presenting three key ways it enhances insights.

First, how AI automates critical processes, optimizing workflows and resource allocation. Second, how AI algorithms improve data quality by detecting and rectifying errors, ensuring reliable insights. Last, how AI enables businesses to make informed decisions by uncovering patterns and making accurate predictions.

Embracing AI in data management provides a competitive advantage, driving sophisticated decision-making and valuable insights across industries. This article will highlight the transformative potential of AI in data management, informing data decision-makers why it is essential to seize this opportunity for growth and success.

About the writer: With more than 20 years of experience in software engineering, Jay Mishra is an expert in product vision and development. Jay is the Chief Operating Officer for Astera Software, where he focuses on product development and strategic planning. Jay holds a Master of Science degree in Computer Science from Virginia Tech and a Bachelor of Science in Mathematics and Computing from the Indian Institute of Technology.

Data: it is the backbone of businesses, enabling informed decision-making, enhanced customer service, and innovation. However, effectively managing data presents challenges, from collection to storage and analysis.

Integrating unstructured data is a challenging task due to its diverse formats and lack of structure. Managing this type of data has historically required extensive manual labor and complex systems to ensure the data is properly extracted. Even with a team of experts, there is still a risk of human error, from missing fields to duplications and inconsistencies.

The rise of artificial intelligence (AI) is revolutionizing data management practices, ushering in a new era of efficiency and efficacy. Large language models such as ChatGPT, Bing, and Google Bard are transforming both the speed at which we can process data, and the way we can use and understand that data.

Just as the advent of Excel revolutionized data processing and analysis, AI represents a new frontier in data management capabilities. While Excel brought the power of spreadsheets to the masses, large language models harness the capabilities of advanced language models to process and analyze data in a conversational manner. Unlike Excel’s structured and formula-based approach, AI’s natural language processing abilities enable users to interact with data in a more intuitive and conversational manner.

Using AI, businesses can now query, explore, and gain insights from their data using everyday language, eliminating the need for complex formulas and technical expertise. This opens up new possibilities for users of all backgrounds to effortlessly leverage data in their decision-making processes.

To Know More, Read Full Article @ https://ai-techpark.com/unlocking-the-power-of-ai/ 

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In AI-Tech Park’s commitment to uncovering the path toward realizing enterprise AI, we recently sat down with Chris Lynch, an esteemed figure in the industry and accomplished Executive Chairman and CEO of AtScale. With a remarkable track record of raising over $150 million in capital and delivering more than $7 billion in returns to investors, Chris possesses invaluable knowledge about what it takes to achieve remarkable results in the fields of AI, data, and cybersecurity.

Please give us a brief overview of AtScale and its origin story. What makes AtScale stand apart from its competitors?

AtScale was founded in 2013 as a highly scalable alternative to traditional OLAP analytics technologies like Microsoft SSAS, Business Objects, Microstrategy, or SAP BW.  However, our true breakthrough came with the enterprise’s shifting data infrastructure to modern cloud data platforms.  AtScale uniquely lets analytics teams deliver “speed of thought” access to key business metrics while fully leveraging the power of modern, elastic cloud data platforms.  Further, what sets AtScale apart is its highly flexible semantic layer.  This layer serves as a centralized hub for governance and management, empowering organizations to maintain control while avoiding overly constraining decentralized analytics work groups.

How do AtScale’s progressive products and solutions further the growth of its clients?

AtScale offers the industry’s only universal semantic layer, allowing our clients to effectively manage all the data that is important and relevant for making critical business decisions within the enterprise. This is so they can drive mission-critical processes off of what matters the most – the data!

To achieve this, AtScale provides a suite of products that enable our end clients to harness the power of their enterprise data to fuel both business intelligence (BI) and artificial intelligence (AI) workloads. We simplify the process of building a logical view of the most significant data by seamlessly connecting to commonly used consumption tools like PowerBI, Tableau, and Excel and cloud data warehouses like Google BigQuery, Databricks, and Snowflake.  

What potential do you think AI and ML hold to transform SMEs and large enterprises? How can companies leverage these modern technologies and streamline their processes?

AI and ML are going to have a profound impact on how we live, conduct our day-to-day business, and shape the global economy. It is imperative for every organization to leverage AI to streamline their operations and processes, improve their costs, and more importantly build and sustain competitive differentiation in the market. But without proper data, AI becomes inefficient and uneventful. The power of those AI models and their predictions rests in the organizational data and needs a universal semantic layer to create AI-ready data.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-chris-lynch/ 

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Kindly brief us about yourself and your role as the Co-CEO at Sinequa.

I’m a serial entrepreneur, business developer and investor inspired by technology that improves the way we work. I’m passionate about human-augmented technologies like AI and machine learning that elevate human productivity and intelligence, rather than replace humans. In 2010, I co-founded Seal Software, a contract analytics company that was the first to use an AI-powered platform to add intelligence, automation, and visualization capabilities to contract data management. During my tenure, I oversaw the company’s fiscal growth and stability, which led to the acquisition of Seal by DocuSign in May 2020. I later served as President and Chief Revenue Officer of Time is Ltd., a provider of a productivity analytics SaaS platform. I joined Sinequa’s board of directors in March 2021, providing strategic planning and oversight during a time of rapid European expansion. With Sinequa’s fast growth, my role also expanded. So, in January 2023, I joined Alexander Bilger – who has successfully served as Sinequa president and CEO since 2005, in a shared leadership role as Co-CEO with the aim to further accelerate Sinequa’s ambitious global growth. Today there is so much innovation happening around the confluence of AI and enterprise search. I can’t imagine a more exciting space right now, and especially with Sinequa as a leading innovator.

In your opinion, how important is it to augment AI and ML in a way that they can be utilized to their fullest potential and not be a substitute for human skills?

We are experiencing a revolution in what can be done with AI, but it’s not going to make humans obsolete. Humans innately seek ways to make their lives easier and therefore tend to trust automation if it simplifies something. But AI isn’t perfect; for all its capabilities, it still makes mistakes. The more complex and nuanced the situation, the more likely AI is to fail, and those are often the situations that are the most critical. So it is important that we don’t rely on AI to automate everything, but use it to augment human ability, and rely on humans to ensure that the right information is being used to drive the right outcomes.

How important is it to leverage the power of AI in order to boost business performance?

I’m confident that AI is going to very quickly become a key differentiator in everything we do. Being able to use AI effectively will be a competitive advantage; not using AI will be a weakness. Perhaps you’ve heard the saying, “AI isn’t going to replace your job. But someone using AI will.” That is a new era that we are entering, and the same holds true for businesses. Those who find how to apply AI in new and creative ways to improve their business – even in the most mundane of areas – are going to create competitive advantages. I believe it’s going to be less and less about the technology and capability of the AI itself, but rather in how the AI is applied. ChatGPT is just the beginning.

Please brief our audience about the emerging trends of the new generation and how you plan to fulfill the dynamic needs of the AI-ML infrastructure.

To Know More, Visit @ https://ai-techpark.com/aitech-interview-with-ulf-zetterberg/ 

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