A naukri.com initiative
Data Analytics News
Pymnts
10h
224
Image Credit: Pymnts
Payment Processing Leads Charge in Modernizing B2B Financial Ecosystems
- Artificial intelligence (AI) has the potential to transform the payment industry, streamlining operations and enhancing efficiency in B2B payments.
- Boost Payment Solutions is actively adopting generative AI (GenAI) to tackle challenges and improve processes, such as fraud detection and automation.
- GenAI can analyze transaction patterns in real-time, identify anomalies, and enhance security by reducing fraud and building customer trust.
- Boost Payment Solutions is setting a new standard for the industry by integrating AI responsibly and innovating across fraud prevention, personalization, and industry-specific solutions.
Read Full Article
13 Likes
Pymnts
20h
81
Image Credit: Pymnts
Hitachi Vantara CTO for AI: What Many Enterprises Overlook That Blocks AI Success
- Companies investing in artificial intelligence will face increasing pressure to demonstrate returns on their investments in 2025 and beyond, according to Hitachi Vantara CTO for AI Jason Hardy.
- AI investment is likely to depend increasingly on demonstrable results.
- Only 13% of CFOs surveyed identified 'very positive' ROI, but most plan to continue investing in AI.
- A fifth of IT leaders say their AI models hallucinate or make things up.
- Only 36% trust their AI outputs more than half of the time.
- Data quality is underestimated by companies plunging into Artificial Intelligence and poor data leads to poor results.
- 76% of IT leaders say their data is unstructured leading to difficulties in organizing it and preparing it for AI use.
- Hitachi Vantara's approach is to let the customer identify the area first which requires automation before organizing the relevant data accordingly.
- Clients are advised to start with use cases at the periphery first before moving to core business functions to minimize risks.
- Hitachi Vantara's approach to helping clients prepare their data varies according to use case requirements.
- Hitachi Vantara is developing its own family of foundation models and focusing on industries where the parent has deep expertise.
Read Full Article
4 Likes
Cloudblog
1d
139
Image Credit: Cloudblog
Introducing BigQuery metastore, a unified metadata service with Apache Iceberg support
- Google has introduced a unified metadata service called BigQuery metastore, which enables a single source of truth for all data processing, is serverless, and supports BigQuery, Apache Spark, Apache Flink and Apache Hive.
- BigQuery metastore has near-unlimited scaleability and works with multiple analytics engines using the Apache Iceberg table format, enabling query processing and DML for data stored in open and proprietary formats across object stores, BigQuery storage, and across analytics runtimes.
- The metastore operates in a no-ops environment, reducing total cost of access and democratizing data for analysts, engineers, and scientists.
- An industry challenge with metadata management is fragmentation across storage systems. However, BigQuery metastore supports open data formats such as Apache Iceberg that are accessible by a variety of processing engines, making it easier for users to find and use data.
- The metastore also has built-in key governance features, such as automated cataloguing, universal search, business metadata, data profiling, data quality, fine-grained access controls, data masking, sharing, data lineage and audit logging.
- BigQuery metastore is the solution for individuals who want to modernize from legacy data lakes to a modern lakehouse architecture, which comprises the benefits of data lakes and data warehouses without having to manage both separately.
- The introduction of the BigQuery metastore means that applications no longer have to maintain multiple copies of data and metadata persisted in various metastores across different processing engines.
- The PySpark script is a prime example of how to use BigQuery metastore-with it, Spark can interact with a BigQuery storage table, a BigQuery table for Apache Iceberg, and a BigQuery external table.
- BigQuery metastore is the serverless, modern solution for metadata management, offering cross-engine capabilities and built-in governance, and can be tried out in the documentation.
- Migration tooling is provided for those interested in migrating from Dataproc Metastore to BigQuery metastore.
Read Full Article
8 Likes
Medium
1d
312
Image Credit: Medium
Series 3: Let Excel Do the Math for You.
- Formulas in Excel allow you to perform calculations quickly and accurately.
- They are like little notes that tell Excel what mathematical operations to perform.
- Cell references are used to point Excel to the numbers involved in the calculation.
- Examples of formulas include addition, subtraction, multiplication, and division.
Read Full Article
18 Likes
Pymnts
1d
175
Image Credit: Pymnts
Visa AI Head Predicts ‘Very Fast’ Timeline for GenAI Integration
- GenAI has the potential to transform businesses in various aspects such as customer support, risk management, and commerce.
- Visa, with its vast transaction data, is well-positioned to leverage GenAI for new innovations in payments.
- Visa has been a pioneer in deploying AI-based technology for risk and fraud management and has invested billions in cutting-edge technology.
- Visa is using GenAI to improve client support, protect its ecosystem, and enhance the shopping experience through personalized recommendations.
Read Full Article
10 Likes
Medium
4d
284
Image Credit: Medium
MICROSOFT EXCEL: A TOOL FOR DATA ANALYTICS
- Excel has built-in tools like formulas, pivot tables, and visualizations that make data analytics easier.
- It can be used by anyone, even those without coding skills, to understand and analyze data.
- Excel is great for quick data checks and small to medium-sized data analysis.
- However, it has limitations with large data files and complex calculations.
Read Full Article
17 Likes
Pymnts
6d
250
Image Credit: Pymnts
ServiceNow to Acquire Cuein to Enhance AI Agents
- ServiceNow plans to acquire Cuein to enhance its AI agents.
- Cuein's expertise in AI native conversation data analysis will help ServiceNow's AI agents understand and process customer interactions.
- The acquisition will enable AI agents to access accurate real-time insights, streamline operations, and accelerate decision-making.
- ServiceNow's Workflow Data Fabric will be enhanced by Cuein's technology, allowing organizations to improve the performance of their AI agents.
Read Full Article
14 Likes
Pymnts
2h
142
Image Credit: Pymnts
CFOs and Treasurers Embrace Leading Role in Organizational Data Monetization
- To monetise the vast amounts of data that businesses now produce, CFOs and treasurers must play a leading role in data-driven processes and planning, according to PYMNTS. Data value management, data resource life-cycle measurement and executive-level data leadership make up the key pillars of a business culture that acknowledges big data as a valuable strategic asset. Among the three, data value realisation involves the deployment of actionable insights that translate to gains in revenue or customer experience improvements. For maximum efficiency, efforts must be aligned with broader business strategies.
- Treasurers have a key role to play in bridging the gap between financial priorities and technological possibilities. Meanwhile, data life-cycle measurement involves measuring the financial impact of data over time, as well as its reuse across different departments and how it contributes to revenue generation and cost savings. By properly tracking and analysing data, businesses can make better informed decisions and allocate resources more effectively.
- Finance teams play a crucial part in data monetisation, providing analytical rigour for measuring the financial and non-financial gains that data initiatives deliver. They also ensure that data projects are prioritised and aligned with a company's broader financial outlook and funding requirements. Smart data management will become even more important as businesses migrate further to the cloud and adopt artificial intelligence technologies.
- At present, 77% of treasurers believe closer collaboration between departments is necessary and to reap the full benefits from data monetisation all participants must share a common approach. CFOs, meanwhile, have a critical role in measuring the potential return on investment in data-oriented initiatives, prioritising the most impactful and setting budgets accordingly.
- Finance teams want to automate their sectors. According to Flashfood CFO Chris Taylor, 'We’re super-focused on automating all the financial flows within the finance function.'
Read Full Article
8 Likes
Medium
1d
158
Earn Money From Freelancing
- Flexibility: Freelancing allows you to work on your own schedule, choosing projects that fit your lifestyle.
- Autonomy: As a freelancer, you are your own boss, making decisions on which projects to take on and how to approach them.
- Unlimited earning potential: Your earnings are directly tied to your skills, experience, and the value you bring to clients.
- Opportunity to work with diverse clients: Freelancing exposes you to various industries, clients, and projects, broadening your professional network and experience.
Read Full Article
9 Likes
Siliconangle
1d
325
Image Credit: Siliconangle
Diesel Labs blends generative AI chat with big-data analysis to create synthetic focus groups for marketing teams
- Diesel Labs Inc. has developed a tool called PanelAI that merges generative AI chat capabilities with its proprietary dataset on consumer attitudes.
- PanelAI provides marketing and media teams with real-time insights from consumers, derived from over 2.2 billion daily signals on various platforms.
- The tool acts as a synthetic focus group, replacing traditional focus groups and surveys to deliver accurate insights into consumer behavior.
- PanelAI combines social media opinions with statistical data analysis, offering a deeper understanding of emerging trends and enabling smarter decisions.
Read Full Article
19 Likes
Medium
1d
135
Image Credit: Medium
Unearthing Patterns in Ordered Data: The Power of the Cochran-Armitage Trend Test
- Researchers often observe patterns in binomial outcomes across ordinal predictors, but these patterns may arise due to random variation, necessitating robust statistical validation.
- This essay explores the Cochran-Armitage trend test through a practical example of a clinical trial evaluating response rates across three dosage levels. The test’s mechanics, visualization techniques, and interpretation of results are demonstrated step-by-step.
- The test identified an apparent upward trend in response rates as the dosage increased. However, the p-value of 0.1228 indicated that the trend was not statistically significant at the 0.05 threshold.
- While visual patterns suggest a potential relationship, the Cochran-Armitage trend test underscores the importance of statistical rigor in trend validation. Further analysis with larger sample sizes or alternative methods may be required to confirm the observed pattern.
Read Full Article
8 Likes
Scientificworldinfo
3d
287
Image Credit: Scientificworldinfo
IBM Data Science Professional Certificate Review
- The IBM Data Science Professional Certificate is a well-known program that provides users with theoretical knowledge and practical applications, making it one of the most sought-after certificates in the world of data science.
- The certificate includes different courses that cover a range of topics, including Python programming for data science, data cleansing, data analysis with Python, and data science methodology, among others.
- One of the standout features of this certificate program is that it is accessible to beginners with different levels of experience in data science.
- This program emphasizes practical learning, where users work on real-world case studies, hands-on projects, build machine learning models, and create visualizations.
- An IBM certificate carries weight in the tech industry, and earning one can increase an individual's credibility as a data science professional.
- Compared to traditional degree programs, the IBM Data Science Professional Certificate is a more affordable way to gain specialized skills in data science.
- Earning the IBM certificate opens doors to various roles, including data scientist, machine learning engineer, AI specialist, marketing analyst, among others.
- To succeed in the program, an individual must set clear goals, engage with the community, take advantage of career services platforms provided by Coursera, and continuously track their progress.
- The program is self-paced, meaning that individuals can learn at their own pace, but it requires a significant investment of time and effort.
- In conclusion, the IBM Data Science Professional Certificate is an accessible and valuable stepping stone for anyone looking to start or advance their career in data science.
Read Full Article
17 Likes
Medium
3d
48
10 Best Reasons You and Your Kids Should Focus on AI in 2025 and Beyond.
- Understanding how AI works allows you and your children to make the most of these technologies while staying informed about their implications.
- Teaching kids the basics of AI early can prepare them for high-demand, lucrative careers in fields like robotics and machine learning.
- Learning about AI helps kids develop critical thinking, problem-solving abilities, and boosts creativity through AI-powered tools.
- Teaching kids about AI means discussing its ethical implications, adapting to a changing world, and empowering them as future innovators.
Read Full Article
2 Likes
Hackernoon
3d
205
Image Credit: Hackernoon
What Kind of Skills Are Required to Become a Data Analyst?
- To become a Data Analyst, one must enjoy working with data, solving problems, and finding stories hidden in numbers.
- Excel, SQL, Python, and Data Visualization Tools are the essentials for a Data Analyst, but a focus on non-technical skills can set you apart.
- Algorithmic thinking, understanding the end-user's needs, clear communication, and defining the problem are the key non-technical skills to focus on.
- Start with small projects, explore free datasets on platforms like Kaggle, and network on LinkedIn to practice.
- Creating a portfolio showcasing your projects can help you stand out as a candidate.
- Remember that every Data Analyst's journey is different, and it's essential to focus on your growth and path.
- Becoming a Data Analyst is a learning and growth journey that requires a mindset of curiosity, problem-solving, and storytelling.
- With practice and patience, anyone can become a Data Analyst!
Read Full Article
12 Likes
Medium
5d
378
Image Credit: Medium
Frequent Pattern Analysis using Association Rule Mining: A Comprehensive Overview
- Frequent Pattern Analysis involves identifying patterns, associations, or correlations within datasets.
- Association Rule Mining is a data mining technique used to discover relationships between variables.
- Association rules indicate associations between items or events based on their co-occurrence.
- Frequent Pattern Analysis and Association Rule Mining have wide-ranging applications but face challenges like scalability and interpretability.
Read Full Article
22 Likes
For uninterrupted reading, download the app