Data Science Connect

JULY 28, 2023

As the Internet of Things (IoT) continues to revolutionize industries and shape the future, data scientists play a crucial role in unlocking its full potential. A recent article on Analytics Insight explores the critical aspect of data engineering for IoT applications.

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Dataversity

OCTOBER 4, 2022

The rise of data lakes and adjacent patterns such as the data lakehouse has given data teams increased agility and the ability to leverage major amounts of data. Constantly evolving data privacy legislation and the impact of major cybersecurity breaches has led to the call for responsible data […].

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Dataversity

AUGUST 15, 2022

If data is the new oil, then high-quality data is the new black gold. Just like with oil, if you don’t have good data quality, you will not get very far. So, what can you do to ensure your data is up to par and […]. You might not even make it out of the starting gate.

Data Observability 52

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Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. Click to learn more about author Brian Platz.

Database 90

Database Data Lakes Data Silos Data Governance 90

The MLOps Blog

JUNE 27, 2023

To provide you with a comprehensive overview, this article explores the key players in the MLOps and FMOps (or LLMOps) ecosystems, encompassing both open-source and closed-source tools, with a focus on highlighting their key features and contributions. Data monitoring tools help monitor the quality of the data.

Machine Learning 134

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Dataversity

DECEMBER 16, 2020

According to IDC, the size of the global datasphere is projected to reach 163 ZB by 2025, leading to the disparate data sources in legacy systems, new system deployments, and the creation of data lakes and data warehouses. Most organizations do not utilize the entirety of the data […].

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Dataversity

JULY 25, 2024

Over the past few years, the industry has increasingly recognized the need to adopt a data lakehouse architecture because of the inherent benefits. This approach improves data infrastructure costs and reduces time-to-insight by consolidating more data workloads into a single source of truth on the organization’s data lake.

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Dataversity

SEPTEMBER 12, 2022

The ways in which we store and manage data have grown exponentially over recent years – and continue to evolve into new paradigms. For much of IT history, though, enterprise data architecture has existed as monolithic, centralized “data lakes.” The post Data Mesh or Data Mess?

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Dataversity

FEBRUARY 10, 2023

For many of these organizations, the path toward becoming more data-driven lies in the power of data lakehouses, which combine elements of data warehouse architecture with data lakes.

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ODSC - Open Data Science

FEBRUARY 24, 2023

While machine learning frameworks and platforms like PyTorch, TensorFlow, and scikit-learn can perform data exploration well, it’s not their primary intent. There are also plenty of data visualization libraries available that can handle exploration like Plotly, matplotlib, D3, Apache ECharts, Bokeh, etc.

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Pickl AI

NOVEMBER 4, 2024

The global Big Data and Data Engineering Services market, valued at USD 51,761.6 This article explores the key fundamentals of Data Engineering, highlighting its significance and providing a roadmap for professionals seeking to excel in this vital field. ETL is vital for ensuring data quality and integrity.

Data Engineer 52

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Alation

JULY 19, 2022

Modern data catalogs surface a wide range of data asset types. For instance, Alation can return wiki-like articles, conversations, and business intelligence objects, in addition to traditional tables. Modern data catalogs also facilitate data quality checks. Communicate and Visualize Results.

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Dataversity

MAY 19, 2023

In the early days of business analysis and underwriting, data was managed with simply a pen and paper and, of course, Excel spreadsheets. As technology has advanced, databases, warehouses, and data lakes have enabled information to be collected, stored, and managed electronically.

Data Lakes 52

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ODSC - Open Data Science

FEBRUARY 14, 2023

It also looks at solutions that make it easier for data teams to hire, manage, retain, and execute effectively using modern data tooling — all while gaining that sought-after efficiency. It also addresses the strategies and best practices for implementing a data mesh.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data Ensuring data quality and integrity Data quality and integrity are essential for accurate data analysis. Data engineers are responsible for ensuring that the data collected is accurate, consistent, and reliable.

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Precisely

MARCH 27, 2023

Staffed by experienced enterprise professionals with an average of nearly 25 tenure years, Precisely Strategic Services is proud to have earned a reputation as a top-tier data-centric management consulting organization. This article offers a few examples that illustrate some of the most popular use cases for data-driven strategic services.

Data Quality 52

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ODSC - Open Data Science

JANUARY 30, 2024

REGISTER NOW Designing and implementing data infrastructure Data engineers are responsible for choosing and configuring the right tools and technologies to store, process, and analyze data. This might involve setting up databases, data lakes, and streaming platforms. Think of it as like being a data doctor.

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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. What is Data Transformation?

Data Quality 52

Data Quality AWS Machine Learning Machine Learning 52

Alation

JUNE 14, 2021

Indeed, automation is a key element to data catalog features, which enhance data security. Selecting a Data Catalog. To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. And, finding data is only half the battle.

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Data Governance Data Lakes Data Classification Data Quality 97

DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Many find themselves swamped by the volume and complexity of unstructured data.

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DagsHub

OCTOBER 23, 2024

Managing unstructured data is essential for the success of machine learning (ML) projects. Without structure, data is difficult to analyze and extracting meaningful insights and patterns is challenging. This article will discuss managing unstructured data for AI and ML projects. How to properly manage unstructured data.

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ODSC - Open Data Science

OCTOBER 20, 2023

HPCC Systems — The Kit and Kaboodle for Big Data and Data Science Bob Foreman | Software Engineering Lead | LexisNexis/HPCC Join this session to learn how ECL can help you create powerful data queries through a comprehensive and dedicated data lake platform.

AI 52

AI AI Data Science Machine Learning 52

Alation

JANUARY 26, 2023

These data requirements could be satisfied with a strong data governance strategy. Governance can — and should — be the responsibility of every data user, though how that’s achieved will depend on the role within the organization. This article will focus on how data engineers can improve their approach to data governance.

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ODSC - Open Data Science

APRIL 3, 2023

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

Analytics 52

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Pickl AI

OCTOBER 17, 2024

It involves extracting data from various sources, transforming it into a suitable format, and loading it into a target system for analysis and reporting. As organisations increasingly rely on data-driven insights, effective ETL processes ensure data integrity and quality, enabling informed decision-making.

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Dataversity

AUGUST 5, 2021

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

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The MLOps Blog

MAY 17, 2023

Often the Data Team, comprising Data and ML Engineers , needs to build this infrastructure, and this experience can be painful. Here are some specific reasons why they are important: Data Integration: Organizations can integrate data from various sources using ETL pipelines. I hope this article was useful for you.

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Dataversity

MARCH 22, 2021

This announcement is interesting and causes some of us in the tech industry to step back and consider many of the factors involved in providing data technology […]. The post Where Is the Data Technology Industry Headed? Click here to learn more about Heine Krog Iversen.

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Data Lakes Data Warehouse Data Quality Data Models 98

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

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The MLOps Blog

MARCH 15, 2023

Data Processing : You need to save the processed data through computations such as aggregation, filtering and sorting. Data Storage : To store this processed data to retrieve it over time – be it a data warehouse or a data lake. This ensures that the data is accurate, consistent, and reliable.

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ODSC - Open Data Science

OCTOBER 15, 2023

Cloudera Cloudera is a cloud-based platform that provides businesses with the tools they need to manage and analyze data. They offer a variety of services, including data warehousing, data lakes, and machine learning. So, what are you waiting for? Get your pass to the ODSC West AI Expo today!

Machine Learning 52

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Dataversity

JANUARY 6, 2021

We live in an era of big data. Amazingly, statistics show that around 90 percent of this data is only two years old. However, Data Management and structuring are notoriously complex. […]. The post The Need for Flexible Data Management: Why Is Data Flexibility So Important?

Big Data 64

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Dataversity

JULY 28, 2022

Every day, businesses create, collect, compile, store, and share exponentially growing amounts of data. But we all know that cyberattacks are on the rise and evolving data privacy legislation has led to the […].

Data Lakes 52

Data Lakes Data Governance Data Quality Machine Learning 52

Dataversity

FEBRUARY 12, 2021

Data has been called the new oil. Now on a trajectory towards increased regulation, the data gushers of yore are being tamed. Data will become trackable, […]. Click to learn more about author Brian Platz.

Data Lakes 52

Data Lakes Data Governance Data Quality Analytics 52

The MLOps Blog

MAY 9, 2023

In this article, you will: 1 Explore what the architecture of an ML pipeline looks like, including the components. To keep concepts simple in this article, you will learn what a typical pipeline looks like without the nuances of real-time or batch constructs. Data validation (writing tests to check for data quality).

ML 98

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Alation

AUGUST 4, 2022

Yet the question remains: How much value have organizations derived from big data? In this article, we’ll take stock of what big data has achieved from a c-suite perspective (with special attention to business transformation and customer experience.). Big Data as an Enabler of Digital Transformation.

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The MLOps Blog

MARCH 21, 2023

Learn from the practical experience of four ML teams on collaboration in this article. Data scientists and machine learning engineers need an infrastructure layer that lets them scale their work without having to be networking experts. This article defines architecture as the way the highest-level components are wired together.

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