ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

Data Integration 98

Data Integration ML ESG Big Data 98

Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

Data Quality 52

Data Quality ETL Machine Learning Data Ingestion 52

Pickl AI

OCTOBER 18, 2023

How to Scale Your Data Quality Operations with AI and ML: In the fast-paced digital landscape of today, data has become the cornerstone of success for organizations across the globe. Every day, companies generate and collect vast amounts of data, ranging from customer information to market trends.

Data Quality 52

Data Quality ML Machine Learning Natural Language Processing 52

Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications.

Data Quality 52

Data Quality Machine Learning Data Science Data Integration 52

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Also Read: Top 10 Data Science tools for 2024.

ETL 40

ETL Data Integration Data Quality Metadata 40

Pickl AI

JUNE 28, 2023

In today’s data-driven world, organizations collect vast amounts of data from various sources. Information like customer interactions, and sales transactions plays a pivotal role in decision-making. But, this data is often stored in disparate systems and formats. Here comes the role of Data Mining.

Data Mining 52

Data Mining Data Integration ETL Data Quality 52

Unite.AI

AUGUST 28, 2024

Challenges of Using AI in Healthcare Physicians, doctors, nurses, and other healthcare providers face many challenges integrating AI into their workflows, from displacement of human labor to data quality issues. Some providers might also disregard ethics and use patient data without permission.

Data Quality 317

Data Quality Algorithm AI AI 317

IBM Journey to AI blog

JANUARY 9, 2024

The entire generative AI pipeline hinges on the data pipelines that empower it, making it imperative to take the correct precautions. 4 key components to ensure reliable data ingestion Data quality and governance: Data quality means ensuring the security of data sources, maintaining holistic data and providing clear metadata.

Data Ingestion 230

Data Ingestion Data Integration Data Quality LLM 230

IBM Journey to AI blog

SEPTEMBER 5, 2024

Everything is data—digital messages, emails, customer information, contracts, presentations, sensor data—virtually anything humans interact with can be converted into data, analyzed for insights or transformed into a product. Managing this level of oversight requires adept handling of large volumes of data.

Metadata 189

Metadata Data Quality Auto-classification DevOps 189

Unite.AI

JULY 19, 2024

That's an AI hallucination, where the AI fabricates incorrect information. The consequences of relying on inaccurate information can be severe for these industries. These tools help identify when AI makes up information or gives incorrect answers, even if they sound believable. What Are AI Hallucination Detection Tools?

LLM 279

LLM AI AI Data Quality 279

AI News

OCTOBER 17, 2024

Data integrity and security emerged as the biggest deterrents to implementing new AI solutions. Executives also reported encountering various AI performance issues, including: Data quality issues (e.g.,

Big Data 249

Big Data AI AI Data Quality 249

Marktechpost

JUNE 5, 2024

In addition, organizations that rely on data must prioritize data quality review. Data profiling is a crucial tool. For evaluating data quality. Data profiling gives your company the tools to spot patterns, anticipate consumer actions, and create a solid data governance plan.

Data Quality 114

Data Quality Metadata Data Integration ETL 114

Unite.AI

OCTOBER 30, 2024

Data quality is another critical concern. AI systems are only as good as the data fed into them. If the input data is outdated, incomplete, or biased, the results will inevitably be subpar. Unfortunately, organizations sometimes overlook this fundamental aspect, expecting AI to perform miracles despite flaws in the data.

Automation 189

Automation AI AI Data Quality 189

Unite.AI

JUNE 12, 2024

Professionals are evaluating AI's impact on security , data integrity, and decision-making processes to determine if AI will be a friend or foe in achieving their organizational goals. The rapid advancement of AI raises questions about data protection, the integrity of AI models, and the safeguarding of proprietary information.

Data Quality 147

Data Quality Automation AI AI 147

IBM Journey to AI blog

DECEMBER 16, 2022

So, instead of wandering the aisles in hopes you’ll stumble across the book, you can walk straight to it and get the information you want much faster. An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more.

Metadata 130

Metadata Data Quality Data Discovery Data Scientist 130

Pickl AI

NOVEMBER 4, 2024

It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. The goal is to ensure that data is available, reliable, and accessible for analysis, ultimately driving insights and informed decision-making within organisations. from 2021 to 2026.

Data Quality 52

Data Quality ETL Data Integration Machine Learning 52

Unite.AI

NOVEMBER 13, 2024

In the coming years, I expect a few key trends to shape the AI and data observability market. Real-time data observability will become more critical as enterprises look to make faster, more informed decisions.

Machine Learning 147

Machine Learning Large Language Models Automation Data Quality 147

Pickl AI

OCTOBER 17, 2024

This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Efficient management of ETL Data is essential for businesses seeking to leverage their information for strategic decision-making.

ETL 52

ETL Data Quality Data Integration Automation 52

Pickl AI

OCTOBER 6, 2024

Understanding these methods helps organizations optimize their data workflows for better decision-making. Introduction In today’s data-driven world, efficient data processing is crucial for informed decision-making and business growth. This phase is crucial for enhancing data quality and preparing it for analysis.

ETL 52

ETL Data Quality Data Integration Big Data 52

Pickl AI

OCTOBER 17, 2024

Summary: The ETL process, which consists of data extraction, transformation, and loading, is vital for effective data management. Following best practices and using suitable tools enhances data integrity and quality, supporting informed decision-making. ETL stands for Extract, Transform, Load.

ETL 52

ETL Explainability Data Integration Data Extraction 52

Unite.AI

MAY 23, 2024

For example, leveraging AI to create a more robust and effective product recommendation and personalization engine requires connecting user data from a CRM and sourcing product data from a Product Information Management (PIM) system. Onboarding data into AI systems is a crucial step that requires careful planning and execution.

AI 269

AI AI AI Engineer Machine Learning 269

IBM Journey to AI blog

AUGUST 23, 2023

So, if we are training a LLM on proprietary data about an enterprise’s customers, we can run into situations where the consumption of that model could be used to leak sensitive information. In-model learning data Many simple AI models have a training phase and then a deployment phase during which training is paused.

Large Language Models 187

Large Language Models Data Discovery LLM AI 187

Pickl AI

OCTOBER 10, 2024

Summary: Data transformation tools streamline data processing by automating the conversion of raw data into usable formats. These tools enhance efficiency, improve data quality, and support Advanced Analytics like Machine Learning.

ETL 52

ETL Data Quality Business Intelligence Big Data 52

Pickl AI

AUGUST 30, 2024

Organisations often undertake data migration during system upgrades, consolidations, or when adopting new technologies. The primary goal is to ensure that data is accurately transferred and remains usable in the new environment. It can be complex, involving various challenges such as data integrity, compatibility, and downtime.

Data Quality 52

Data Quality Data Integration Automation Machine Learning 52

Unite.AI

DECEMBER 5, 2023

In BI systems, data warehousing first converts disparate raw data into clean, organized, and integrated data, which is then used to extract actionable insights to facilitate analysis, reporting, and data-informed decision-making. Data Sources: Data sources provide information and context to a data warehouse.

Metadata 162

Metadata Big Data ETL Data Mining 162

Unite.AI

MAY 15, 2024

This isn’t just about having a place to store data; it’s about creating an organized, efficient system capable of managing and processing vast amounts of information as the project’s complexity grows. Teams should be continually updating their databases to reflect the most current information.

Large Language Models 147

Large Language Models Generative AI Data Quality AI Architect 147

Pickl AI

AUGUST 31, 2023

Introduction The presence of large volumes of data within organisations requires effective sorting and analysing ensuring that decision-making is highly credible. Almost all organisations nowadays make informed decisions by leveraging data and analysing the market effectively. What is Data Profiling in ETL?

ETL 52

ETL Data Quality Data Integration Metadata 52

Pickl AI

JULY 19, 2023

Every business, irrespective of the niche of operations is harnessing the power of data and make their strategies result-oriented. As compared to the earlier times, businesses are inundated with vast amounts of information. To harness this information in the best interest of the business, it is imperative to filter quality inputs.

Explainability 40

Explainability Data Quality Data Integration Automation 40

Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data. What is Data Observability?

Data Quality 52

Data Quality Metadata Automation Data Science 52

Pickl AI

JULY 8, 2024

It covers best practices for ensuring scalability, reliability, and performance while addressing common challenges, enabling businesses to transform raw data into valuable, actionable insights for informed decision-making. What are Data Pipelines?

ETL 52

ETL Data Quality Data Integration Automation 52

Marktechpost

OCTOBER 28, 2024

Knowledge Graph (KG) synthesis is gaining traction in artificial intelligence research because it can construct structured knowledge representations from expansive, unstructured text data. KGs effectively link and organize information, enabling models to process and answer intricate queries more accurately.

LLM 106

LLM Inference Engine Large Language Models Artificial Intelligence 106

Marktechpost

JULY 7, 2024

Age and Gender Targeting: Ads are delivered based on demographic information such as age and gender, which is collected during user registration or inferred from user behavior. Key components of this model include: User Tower: Captures and encodes user features such as demographic information and browsing history.

Algorithm 103

Algorithm Neural Network Metadata Large Language Models 103

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making.

Data Ingestion 52

Data Ingestion ETL Data Quality Data Integration 52

Pickl AI

MAY 30, 2024

These figures underscore the significance of comprehending data methodologies for anyone navigating the digital landscape. Understanding Data Science Data Science involves analysing and interpreting complex data sets to uncover valuable insights that can inform decision-making and solve real-world problems.

Data Analysis 52

Data Analysis Data Science Data Scientist Data Quality 52

Pickl AI

OCTOBER 2, 2024

Summary: Artificial Intelligence (AI) is revolutionising Genomic Analysis by enhancing accuracy, efficiency, and data integration. Despite challenges like data quality and ethical concerns, AI’s potential in genomics continues to grow, shaping the future of healthcare.

Neural Network 52

Neural Network Artificial Intelligence Artificial Intelligence Deep Learning 52

Pickl AI

SEPTEMBER 12, 2024

Summary: This comprehensive guide explores data standardization, covering its key concepts, benefits, challenges, best practices, real-world applications, and future trends. By understanding the importance of consistent data formats, organizations can improve data quality, enable collaborative research, and make more informed decisions.

Data Quality 52

Data Quality Machine Learning Automation Artificial Intelligence 52

Unite.AI

NOVEMBER 11, 2024

A cornerstone of this strategy is our commitment to data integrity and diversity, evident in our significant investment in privacy and compliance measures and dataset curation. Jumio has made substantial investments in both time and financial resources to navigate the complex and ever-changing landscape of AI regulations.

AI 162

AI AI Machine Learning Natural Language Processing 162