Tag: Data Management

As we have stepped into the digital world, data science is one of the most emerging technologies in the IT industry, as it aids in creating models that are trained on past data and are used to make data-driven decisions for the business.

With time, IT companies can understand the importance of data literacy and security and are eager to hire data professionals who can help them develop strategies for data collection, analysis, and segregation. So learning the appropriate data science skills is equally important for budding and seasoned data scientists to earn a handsome salary and also stay on top of the competition.

In this article, we will explore the top 10 data science certifications that are essential for budding or seasoned data scientists to build a strong foundation in this field.

Data Science Council of America (DASCA) Senior Data Scientist (SDS)

The Data Science Council of America’s (DASCA) Senior Data Scientist (SDS) certification program is designed for data scientists with five or more years of professional experience in data research and analytics. The program focuses on qualified knowledge of databases, spreadsheets, statistical analytics, SPSS/SAS, R, quantitative methods, and the fundamentals of object-oriented programming and RDBMS. This data science program has five trackers that will rank the candidates and track their requirements in terms of their educational and professional degree levels.

IBM Data Science Professional Certificate

The IBM Data Science Professional Certificate is an ideal program for data scientists who started their careers in the data science field. This certification consists of a series of nine courses that will help you acquire skills such as data science, open source tools, data science methodology, Python, databases and SQL, data analysis, data visualization, and machine learning (ML). By the end of the program, the candidates will have numerous assignments and projects to showcase their skills and enhance their resumes.

Open Certified Data Scientist (Open CDS)

The Open Group Professional Certification Program for the Data Scientist Professional (Open CDS) is an experienced certification program for candidates who are looking for an upgrade in their data science skills. The programs have three main levels: level one is to become a Certified Data Scientist; level two is to acquire a Master’s Certified Data Scientist; and the third level is to become a Distinguished Certified. This course will allow data scientists to earn their certificates and stay updated about new data trends.

Earning a certification in data science courses and programs is an excellent way to kickstart your career in data science and stand out from the competition. However, before selecting the correct course, it is best to consider which certification type is appropriate according to your education and job goals.

To Know More, Read Full Article @ https://ai-techpark.com/top-5-data-science-certifications-to-boost-your-skills/ 

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Deep Learning in Big Data Analytics

Explainable AI Is Important for IT

Explore Category - AI Identity and access management

As we have stepped into the realm of 2024, the artificial intelligence and data landscape is growing up for further transformation, which will drive technological advancements and marketing trends and understand enterprises’ needs. The introduction of ChatGPT in 2022 has produced different types of primary and secondary effects on semantic technology, which is helping IT organizations understand the language and its underlying structure.

For instance, the semantic web and natural language processing (NLP) are both forms of semantic technology, as each has different supportive rules in the data management process.

In this article, we will focus on the top four trends of 2024 that will change the IT landscape in the coming years.

Reshaping Customer Engagement With Large Language Models

The interest in large language models (LLMs) technology came to light after the release of ChatGPT in 2022. The current stage of LLMs is marked by the ability to understand and generate human-like text across different subjects and applications. The models are built by using advanced deep-learning (DL) techniques and a vast amount of trained data to provide better customer engagement, operational efficiency, and resource management.

However, it is important to acknowledge that while these LLM models have a lot of unprecedented potential, ethical considerations such as data privacy and data bias must be addressed proactively.

Importance of Knowledge Graphs for Complex Data

The introduction of knowledge graphs (KGs) has become increasingly essential for managing complex data sets as they understand the relationship between different types of information and segregate it accordingly. The merging of LLMs and KGs will improve the abilities and understanding of artificial intelligence (AI) systems. This combination will help in preparing structured presentations that can be used to build more context-aware AI systems, eventually revolutionizing the way we interact with computers and access important information.

As KGs become increasingly digital, IT professionals must address the issues of security and compliance by implementing global data protection regulations and robust security strategies to eliminate the concerns.  

Large language models (LLMs) and semantic technologies are turbocharging the world of AI. Take ChatGPT for example, it's revolutionized communication and made significant strides in language translation.

But this is just the beginning. As AI advances, LLMs will become even more powerful, and knowledge graphs will emerge as the go-to platform for data experts. Imagine search engines and research fueled by these innovations, all while Web3 ushers in a new era for the internet.

To Know More, Read Full Article @ https://ai-techpark.com/top-four-semantic-technology-trends-of-2024/ 

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Explainable AI Is Important for IT

Chief Data Officer in the Data Governance

News - Synechron announced the acquisition of Dreamix

Data has always been at the core of a business, which explains the importance of data and analytics as core business functions that often need to be addressed due to a lack of strategic decisions. This factor gives rise to a new technology of stitching data using data fabrics and data mesh, enabling reuse and augmenting data integration services and data pipelines to deliver integration data.

Further, data fabric can be combined with data management, integration, and core services staged across multiple deployments and technologies.

This article will comprehend the value of data fabric architecture in the modern business environment and some key pillars that data and analytics leaders must know before developing modern data management practices.

The Evolution of Modern Data Fabric Architecture

Data management agility has become a vital priority for IT organizations in this increasingly complex environment. Therefore, to reduce human errors and overall expenses, data and analytics (D&A) leaders need to shift their focus from traditional data management practices and move towards modern and innovative AI-driven data integration solutions.

In the modern world, data fabric is not just a combination of traditional and contemporary technologies but an innovative design concept to ease the human workload. With new and upcoming technologies such as embedded machine learning (ML), semantic knowledge graphs, deep learning, and metadata management, D&A leaders can develop data fabric designs that will optimize data management by automating repetitive tasks.

Key Pillars of a Data Fabric Architecture

Implementing an efficient data fabric architecture needs various technological components such as data integration, data catalog, data curation, metadata analysis, and augmented data orchestration. Working on the key pillars below, D&A leaders can create an efficient data fabric design to optimize data management platforms.

Collect and Analyze All Forms of Metadata

To develop a dynamic data fabric design, D&A leaders need to ensure that the contextual information is well connected to the metadata, enabling the data fabric to identify, analyze, and connect to all kinds of business mechanisms, such as operational, business processes, social, and technical.

Convert Passive Metadata to Active Metadata

IT enterprises need to activate metadata to share data without any challenges. Therefore, the data fabric must continuously analyze available metadata for the KPIs and statistics and build a graph model. When graphically depicted, D&A leaders can easily understand their unique challenges and work on making relevant solutions.

To Know More, Read Full Article @ https://ai-techpark.com/data-management-with-data-fabric-architecture/ 

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Artificial Intelligence and Sustainability in the IT

Explainable AI Is Important for IT

Neda, please share some key milestones and experiences from your professional journey that have shaped your perspective and approach as Chief Product Officer at Stibo Systems.

I have the honor of mentoring a couple of young leaders, and they ask this question a lot. The answer I always give is that I approach each day as an opportunity to learn, so it’s difficult to pinpoint a specific milestone. However, there have been some crucible moments where I made radical decisions, and I think those moments have influenced my journey. One of them was my shift towards computer science. Despite having a background in linguistics and initially aspiring to be a teacher, I took a complete shift and decided to explore computer science. Programming was initially intimidating for me, and I had always tried to avoid math throughout my student life. I saw myself more as an art and literature person, and that gutsy shift turned out to be a great decision in the long term. The decision was made by me, but it wouldn’t have turned into a success without support from my mentors and leaders – it’s super important to have champions around you to guide you, especially early in your career.

Another significant moment was when I accepted a consulting job that involved phasing out legacy systems. This required negotiating with users who would lose functionalities they had been using for years. These conversations were often challenging, and I was tempted to quit. However, I made the decision to stay and tackle the problem with a more compassionate approach towards the application users. It was during this time that I truly understood the nature of change management in the product development process. People find it difficult to let go of their routines and what has made them successful. The more successful users are with their apps, the less likely they are to embrace change. However, sometimes solutions become outdated and need to be replaced – plain and simple. The challenge is how to build a changing product while ensuring that users come along. This story applies to Stibo Systems. We have been around for over 100 years and have managed to transform our business. Stibo Systems is a perfect example of how to build lasting products, be open to change and transformation and make sure you aren’t leaving any customers behind.

Could you provide an overview of Stibo Systems’ mission and how it aligns with the concept of “better data, better business, better world”?

Our heritage extends far back, but we are a cutting-edge technology company. We specialize in delivering data management products that empower companies to make informed decisions, resulting in remarkable outcomes. This approach not only contributes to our sustainable growth but also supports our profitability, allowing us to reinvest and expand.

Our mission statement encapsulates our business ethos – one with a strong sense of conscientiousness. Our primary focus revolves around doing what’s right for our customers, employees and the environment. Customer satisfaction is at the forefront of our priorities, evident in our high software license renewal rates, a testament to our commitment to delivering top-notch products and services.

Moreover, we hold a unique position in the market as one of the few major companies headquartered in Europe. Europe is facing increasing pressure to embrace sustainable practices, and we are actively engaged in leading this transformation.

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

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Future of QA Engineering

CIOs to Enhance the Customer Experience

In the early 2000s, many companies and SMEs had one or more C-suites that were dedicated to handling the IT security and compliance framework, such as the Chief Information Security Officer (CISO), Chief Information Officer (CIO), and Chief Data Officer (CDO). These IT leaders used to team up as policymakers and further implement rules and regulations to enhance company security and fight against cyber security.

But looking at the increased concerns over data privacy and the numerous techniques through which personal information is collected and used in numerous industries, the role of chief privacy officer, or CPO, has started playing a central role in the past few years as an advocate for employees and customers to ensure a company’s respect for privacy and compliance with regulations. 

The CPO’s job is to oversee the security and technical gaps by improving current information privacy awareness and influencing business operations throughout the organization. As their role relates to handling the personal information of the stakeholders, CPOs have to create new revenue opportunities and carry out legal and moral procedures to guarantee that employees can access confidential information appropriately while adhering to standard procedures.

How the CISO, CPO, and CDO Unite for Success

To safeguard the most vulnerable and valuable asset, i.e., data, the IT c-suites must collaborate to create a data protection and regulatory compliance organizational goal for a better success rate.

Even though the roles of C-level IT executives have distinct responsibilities, each focuses on a single agenda of data management, security, governance, and privacy. Therefore, by embracing the power of technology and understanding the importance of cross-functional teamwork, these C-level executives can easily navigate the data compliance and protection landscape in their organizations.

For a better simplification of the process and to keep everyone on the same page, C-suites can implement unified platforms that will deliver insights, overall data management, and improvements in security and privacy.

Organizational data protection is a real and complex problem in the modern digitized world. According to a report by Statista in October 2020, there were around 1500 data breaching cases in the United States where more than 165 million sensitive records were exposed. Therefore, to eliminate such issues, C-level leaders are required to address them substantially by hiring a chief privacy officer (CPO). The importance of the chief privacy officer has risen with the growth of data protection in the form of security requirements and legal obligations.

To Know More, Read Full Article @ https://ai-techpark.com/data-privacy-with-cpos/

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Automated Driving Technologies Work

Ethics in the Era of Generative AI

We believe that the journey of developing software is as tough as quality assurance (QA) engineers want to release high-quality software products that meet customer expectations and run smoothly when implemented into their systems. Thus, in such cases, quality assurance (QA) and software testing are a must, as they play a crucial role in developing good software.

Manual testing has limitations and many repetitive tasks that cannot be automated because they require human intelligence, judgment, and supervision.

As a result, QA engineers have always been inclined toward using automation tools to help them with testing. These AI tools can help them understand problems such as finding bugs faster, and more consistently, improving testing quality, and saving time by automating routine tasks.

This article discusses the role of AI in the future of QA engineering. It also discusses the role of AI in creating and executing test cases, why QA engineers should trust AI, and how AI can be used as a job transformer.

The Role of AI in Creating and Executing Test Cases

Before the introduction of AI (artificial intelligence), automation testing and quality assurance were slow processes with a mix of manual and automatic processes.

Earlier software was tested using a collection of manual methodologies, and the QA team tested the software repetitively until and unless they achieved consistency, making the whole method time-consuming and expensive.

As software becomes more complex, the number of tests is naturally growing, making it more and more difficult to maintain the test suite and ensure sufficient code coverage.

AI has revolutionized QA testing by automating repetitive tasks such as test case generation, test data management, and defect detection, which increases accuracy, efficiency, and test coverage.

Apart from finding bugs quickly, the QA engineers use AI by using machine learning (ML) models to identify problems with the tested software. The ML models can analyze the data from past tests to understand and identify the patterns of the programs so that the software can be easily used in the real world.

AI as a Job Transformer for QA Professionals

Even though we are aware that AI has the potential to replace human roles, industrialists have emphasized that AI will bring revolutionary changes and transform the roles of QA testers and quality engineers.

Preliminary and heavy tasks like gathering initial ideas, research, and analysis can be handled by AI. AI assistance can be helpful in the formulation of strategies and the execution of these strategies by constructing a proper foundation.

The emergence of AI has brought speed to the process of software testing, which traditionally would take hours to complete. AI goes beyond saving mere minutes; it can also identify and manage risks based on set definitions and prior information.

To Know More, Read Full Article @ https://ai-techpark.com/ai-in-software-testing/

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Revolutionize Clinical Trials through AI

AI Impact on E-commerce

In recent years, automation and artificial intelligence (AI) have witnessed a surge in popularity, and it’s anticipated to expand as organizations become more dependent on AI solutions to address issues. Numerous tech giants, like Amazon, Apple, and Alibaba, have already started to explore the possibilities of implementing AI and robotics in their organizations.

The introduction of robots into the workplace is set to alter how C-level decision-makers will do business, as they need to share space with robots as coworkers and learn new skills as robots will gradually take over tedious and dangerous tasks on behalf of their employees. There will be a shift in job responsibilities and obligations, creating bandwidth for strategic planning for better business development in sections where robotics are not utilized. Functional leaders in customer-facing roles may identify the best methods to serve clients and use automation to deliver personalized products and services on demand.

Robotics is becoming a game changer in various industries throughout the world.

Chief Operating Officers (COOs)

COOs will play an important role in transforming the workplace by integrating AI and robotics, creating a digital strategy for automating services, and streamlining operations. Thus, COOs will drive and manage the organization’s transformation into a human-robot workforce; however, they must update their knowledge of technologies by understanding the changes and how they can affect the business. For instance, in a manufacturing company, the role of COOs will be to assess the need for automation technologies like IoT and blockchain in a department. After evaluation, they should come up with an investment strategy by analyzing how AI and robots will reshape the manufacturing industry and streamline the supply chain.

Chief Information Officers (CIOs)

CIOs will have to adjust to technology issues and work closely with other C-suits as they navigate a new landscape of risk and compliance. They will have the liberty to explore and evaluate the areas of data management, analytics, and cybersecurity. With automation technology and robot workers having a positive impact on the organization, CIOs will witness changes in function becoming more deeply integrated.

Other tech leaders, like CTOs and CDOs, may be joined by Chief Robotics Officers (CROs), who will help in navigating how robots will perform, providing robust road maps, and setting strategies for future developments.

Robotics and artificial intelligence (AI) will change the workplace as some job roles will be replaced by robots and automation, but the technology will also lead to the creation of new jobs and highly valued responsibilities. This development will also affect the C-suite, as robots will minimize their responsibilities and help in creating robust strategies in this digital era. Large-scale enterprises and SMEs must prepare their employees for collaboration with new technologies by providing adequate L&D opportunities, upskilling, reskilling, and giving them the bandwidth to accept the change.
To Know More, Read Full Article @ https://ai-techpark.com/robotics-is-changing-the-roles-of-c-suites/

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Diversity and Inclusivity in AIDigital Twins Shaping Industries

In the ever-evolving landscape of technology, the rise and implementation of hybrid cloud computing solutions have become pivotal in reshaping the future of IT infrastructure. As large-scale businesses strive to increase efficiency, reduce latency, and enhance stability, IT professionals adopt this dynamic technology. Cloud technologists believe hybrid clouds may be better for operational efficiency, security, faster application development, improved business insights, and better resiliency.

Let’s take a closer look by understanding the hybrid cloud with a few examples, its key benefits, and its importance in implementing a hybrid cloud in businesses.

What are Hybrid Cloud?

A hybrid cloud is an amalgamation of different cloud computing environments, like public cloud and private cloud infrastructure, which helps organizations compute, network, and store resources in various cloud worlds according to their needs. IT professionals define hybrid cloud computing as flexible as it helps businesses have the autonomy to choose where the data can reside based on performance, compliance requirements, and security.

Let’s take a look at a few examples of where hybrid cloud computing can be implemented:

Several examples emphasize the versatility of implementing hybrid cloud computing in business. For example, a healthcare organization can securely store its patient records and other confidential reports on its private cloud while using the public cloud for hosting websites. Similar to e-commerce companies, utilize a hybrid cloud model to handle peak traffic during holiday sales without compromising customer data security.

Furthermore, the adoption of a hybrid cloud model fosters innovation, which empowers organizations by leveraging legacy systems and modern technologies. Here are some best practices that will help businesses adopt this cloud model:

Best Practices for Hybrid Cloud Adoption

Comprehensive Cloud Strategy

Businesses should develop a comprehensive hybrid cloud strategy that aligns with their business objectives which encompass workload assessment, cloud provider selection, compliance measures, data management, and security protocols.

Robust Governance and Monitoring

Implementing robust governance frameworks and a continuous monitoring process is crucial, which includes tracking resource usage, ensuring compliance, managing costs, and enforcing security policies across all cloud environments.

Employee Training and Skill Development

The successful adoption of the hybrid cloud model requires a skilled workforce qualified to manage complex cloud infrastructure. So organizations should invest in training employees and enroll them in skill development programs to equip them with the necessary expertise in the hybrid cloud model.

To Know More, Read Full Article @ https://ai-techpark.com/power-of-hybrid-cloud-computing/

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Information Security and the C-suiteAutomated Driving Technologies Work

In the ever-evolving world of retail, the holiday season presents unique challenges and opportunities for retailers. As consumer exertion surges, retailers have to be interactive with their customers, both online and in-store. To meet such demands effectively, embracing interactive and unified technology solutions is a strategic imperative for retailers to meet customers’ expectations and generate more sales. This article delves into the crucial aspects of interactive and unified technology in holiday customer service for retailers.

Proactive Message

Proactive order updates, delivery notifications, and personalized recommendations can be sent to customers via SMS, online messaging apps, or push notifications to keep them in the loop. This proactive approach builds trust and reduces unnecessary interactions, freeing up human agents for more complex issues.

Connect the Dots for a Seamless Journey for Unified Technology

Implementing a unified solution in retail streamlines operations enhances the customer experience, and optimizes resource utilization effectively. This section will delve into the practical steps for seamlessly integrating unified technology this holiday season:

Omnichannel Integration

Embracing an omnichannel integration strategy ensures a consistent customer experience across mobile applications, websites, and physical stores. A unified interface allows customers to seamlessly transition between channels.

Feedback Mechanism

Establishing a feedback mechanism to gather insight from customers helps in observing and experimenting with a unified solution to further refine it. With an adaptive approach based on the real world, this feedback is important for continuous improvement.

After learning about the types of interactive and unified technology solutions retailers can implement in their businesses, let’s further dive into how these technologies will help retailers this holiday season.

As retailers gear up for the holiday rush, embracing interactive customer support platforms and unified data management can change the customer service landscape. Investing in these solutions will ease the holiday rush and build long-lasting customer loyalty. So, as the holiday season approaches, these potential technologies will make your customers happy and orchestrate better sales and higher revenue.

To Know More, Read Full Article @ https://ai-techpark.com/interactive-and-unified-in-technology/

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AI in Medical Imaging: Transforming Healthcare

AI and RPA in Hyper-automation Maximize your growth potential with the seasoned experts at SalesmarkGlobal, shaping demand performance with strategic wisdom.

AI and AIOps have been transforming the future of the workplace and IT operations, which accelerates digital transformations. The AIOps stands out as it uses machine learning (ML) and big data tracking, such as root cause analysis, event correlations, and outlier detection. According to the survey, large organizations have been solely relying on AIOps to track their performance. Thus, it is an exciting time for implementing AIOps that can help software engineers, DevOps teams, and other IT professionals to serve quality software and improve the effectiveness of IT operations for their companies.

Adoption of AIOps

Most companies are in the early stages of adopting AIOps to analyze applications and machine learning to automate and improve their IT operations. AIOps have been adopted amongst diverse industries, and more enterprises are adopting it to digitally transform their businesses and simplify complex ecosystems with the help of interconnected apps, services, and devices. AIOps have the potential to tackle complexities that are often unnoticed by IT professionals or other departments in a company. Therefore, AIOps solutions enhance operational efficiency and prevent downtime, which makes work easier.

Numerous opportunities can change the way AIOps has been incorporated into the company. To do so, businesses and IT professionals should be aware of appropriate trends and best practices to embrace AIOps technologies. Let’s take a closer look at these topics:

Best Practices of AIOps

To get the most out of AIOps, DevOps engineers and other IT professionals can implement the following practices:

Suitable Data Management

DevOps engineers must be aware that ill-managed data often gives undesired output and affects decision-making. Thus, for a suitable outcome, you should ensure that the gathered data is properly sorted, clean, and classified for seamless data monitoring and browse data through a large database for your enterprise.

Right Data Security

The security of user data is essential for your company, as it is under the guidance of data protection regulation agencies that can impose fines if the data is misused. The DevOps and IT engineers can ensure that the data is properly safeguarded and used within their control to avoid data breaches.

Appropriate Use of Available AI APIs

AIOps’s main aim is to improve the productivity of IT operations with the help of artificial intelligence. Therefore, the IT teams should look for great AI-enabled APIs that improve the tasks they have to accomplish.

To Know More, Read Full Article @ https://ai-techpark.com/future-of-aiops/ 

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Importance of AI Ethics

AI and RPA in Hyper-automation

Maximize your growth potential with the seasoned experts at SalesmarkGlobal, shaping demand performance with strategic wisdom.