Precisely

SEPTEMBER 6, 2023

Simply put, data catalogs offer an inventory of data assets, a common definition of what the data means, and a shared understanding of how the data can be used. Developing a data catalog is a time-consuming process, made simpler and more manageable with the right technology tools.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

Monte Carlo

AUGUST 9, 2023

Integration tools (Fivetran, Matillion) help extract data from internal and external sources and load it into a data warehouse. Data warehouses/lakes/lakehouses (Redshift, BigQuery, Snowflake, Databricks) offer large-scale, optimized storage for structured or unstructured data, along with the ability to run complex analytical queries.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Pipeline 52

Snowflake

SEPTEMBER 19, 2023

AI unlocks new data use cases. With the ability to handle unstructured data types and larger volumes of data, AI gives us the tools to tackle more complex, exciting problems. And I would definitely agree that, in my mind at least, this will have a big, big impact on our world, perhaps even bigger than the internet.

Machine Learning 95

Machine Learning Unstructured Data Data Analytics Government 95

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. But what does that mean for the roles of data engineers and data scientists going forward?

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Towards Data Science

APRIL 6, 2023

Data types : Anomaly detection looks different depending on if the data is structured, semi-structured, or unstructured, so it’s important to know what you’re working with. When it comes to detecting anomalies in unstructured data (e.g.,

Unstructured Data 80

Unstructured Data Metadata Data Coding 80

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Education 62

Education Unstructured Data Data Lake Data Warehouse 62

DareData

JANUARY 30, 2023

This can involve extracting data from various sources, such as files, operational databases, APIs or IoT data, and transforming it into a format that is suitable for storage and analysis. This can definitely be a complex process, as it often involves dealing with large volumes of data, handling errors and exceptions.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Cloudera

AUGUST 16, 2021

Hundreds of built-in processors make it easy to connect to any application and transform data structures or data formats as needed. Since it supports both structured and unstructured data for streaming and batch integrations, Apache NiFi is quickly becoming a core component of modern data pipelines. and later).

Cloud 119

Cloud Unstructured Data Utilities Metadata 119

Data Engineering Weekly

JUNE 4, 2023

[link] LlamaIndex: Combining Text-to-SQL with Semantic Search for Retrieval Augmented Generation A query engine can leverage the expressivity of SQL over structured data and join it with unstructured context from a vector database - The future of data processing. link] Grab: PII masking for privacy-grade machine learning.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

Snowflake

MAY 1, 2023

“We leverage Snowflake’s core compute and storage capabilities to make the single source of data into a single source of business logic.” With a single definition for customer journey KPIs, At-Bay can provide its business users with consistency and flexibility.

Insurance 102

Insurance Unstructured Data Python Building 102

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). What does DDE entail? Under General Settings define a cluster name.

Cloud Storage 68

Cloud Storage Unstructured Data AWS Analytics Application 68

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Knowledge Hut

APRIL 26, 2024

Let's take a look at all the fuss about data science , its courses, and the path to the future. What is Data Science? In order to discover insights and then analyze multiple structured and unstructured data, Data Science requires the use of different instruments, algorithms and principles.

Data Science 52

Data Science Machine Learning Hadoop Programming Language 52

Cloudera

JANUARY 28, 2022

As firms more and more align towards a hybrid data cloud to balance their business needs, there is another layer of decisioning – private cloud, public cloud, multi-cloud. Let’s start with our definition of a hybrid data cloud. Simple, consistent and intuitive experience for data users and developers.

Cloud 113

Cloud Banking Data Governance Government 113

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Companies need more than definitions.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Monte Carlo

FEBRUARY 15, 2023

Data can be loaded using a loading wizard, cloud storage like S3, programmatically via REST API, third-party integrators like Hevo, Fivetran, etc. Data can be loaded in batches or can be streamed in near real-time. Structured, semi-structured, and unstructured data can be loaded.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Companies need more than definitions.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Companies need more than definitions.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

Knowledge Hut

APRIL 25, 2024

You'll be better able to comprehend the complex ideas in this field if you have a solid understanding of the characteristics of big data in data analytics and a list of essential features for new data platforms. What Are the Different Features of Big Data Analytics?

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Cloudera

OCTOBER 7, 2021

Also included, business and technical metadata, related to both data inputs / data outputs, that enable data discovery and achieving cross-organizational consensus on the definitions of data assets.

Architecture 124

Architecture Metadata Government Kafka 124

Knowledge Hut

JULY 3, 2023

From sentiment analysis to language comprehension, NLP engineers are shaping the future of AI and enabling businesses to make informed decisions based on the vast amount of unstructured data available today. In this article, we'll have a closer look into the NLP engineer salary ranges across companies and geographies.

Engineering 52

Engineering Unstructured Data Certification Computer Science 52

U-Next

SEPTEMBER 19, 2022

If you are prepared to put in the required time and effort and are open to learning new things, you’ll surely become a successful Data Scientist. The opportunities for Data Scientists are unending. Enterprises in all fields definitely would want to employ people with more skills.

Data Science 40

Data Science Programming Language Unstructured Data Data Mining 40

Cloudera

OCTOBER 21, 2020

The insurance companies disagree on potential coverage under the commercial property policies, citing that coverage definitions put in place before the pandemic, or its implications, were widely understood. . Using these forms of structured and unstructured data can unlock new insights, both in isolation and in combination with each other.

Insurance 72

Insurance Unstructured Data Hospitality Media 72

Grouparoo

JANUARY 11, 2022

Difference Between Data Warehouse and Data Lake When looking at the difference between data lake and data warehouse, the following key properties distinguish data lakes vs data warehouses. This resource-heavy process will restrict access to the data during the transformation process.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Knowledge Hut

JUNE 23, 2023

Data warehousing to aggregate unstructured data collected from multiple sources. Data architecture to tackle datasets and the relationship between processes and applications. What is the difference between a data engineer and a data scientist? What’s the Demand for Data Engineers? What is COSHH?

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

ProjectPro

FEBRUARY 16, 2023

Category Business Intelligence (BI) Artificial Intelligence (AI) Definition A set of processes, architectures, and technologies that convert raw data into meaningful and useful information for business analysis purposes. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Edureka

JANUARY 18, 2024

For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? Data science is the study of data to extract knowledge and insights from structured and unstructured data using scientific methods, processes, and algorithms.

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

DECEMBER 22, 2023

Statistics are used by data scientists to collect, assess, analyze, and derive conclusions from data, as well as to apply quantifiable mathematical models to relevant variables. Microsoft Excel An effective Excel spreadsheet will arrange unstructured data into a legible format, making it simpler to glean insights that can be used.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

Knowledge Hut

MARCH 15, 2024

5) AZ-204: Microsoft Azure Developer Associate Developers working on cloud projects in all stages—from requirements, definition, and design through development, deployment, and maintenance to performance tuning and monitoring—are an ideal group for this Professional Certificate.

Cloud Computing 52

Cloud Computing Algorithm Certification SQL 52

Monte Carlo

JUNE 2, 2021

The unique challenge of observability in data lakes For teams that use Databricks to manage their data lakes and run ETL and analysis, data quality issues prove especially challenging. Data lakes almost always contain larger data sets, often with massive amounts of unstructured data.

Data Lake 52

Data Lake Machine Learning Unstructured Data Datasets 52

ProjectPro

FEBRUARY 8, 2023

AWS Glue then creates data profiles in the catalog, a repository for all data assets' metadata, including table definitions, locations, and other features. Let us look at some significant reasons that make AWS Glue a popular serverless data integration service across organizations worldwide. Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

Grouparoo

NOVEMBER 16, 2021

This is where data transformation can come to the rescue. What is Data Transformation Simply speaking, the data transformation definition is the process of converting data from diverse sources into a standard format that supports its analysis.

Data Mining 52

Data Mining Raw Data ETL Tools Unstructured Data 52

Knowledge Hut

JUNE 20, 2023

Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world. Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 22, 2023

They also collaborate with other Azure technologies to develop, deploy, and manage data pipelines and data-driven applications, such as Azure Functions, Azure Kubernetes Service, and Azure DevOps. Is Azure Data Engineer Certification Worth It? A profession in Azure data engineering can be satisfying even when it is challenging.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

DataKitchen

APRIL 13, 2021

Because it is such a new category, both overly narrow and overly broad definitions of DataOps abound. However, these solutions are independent components of the data toolchain that collect, store, transform, visualize, and govern the data running through the pipeline. DataOps is great, but use our tool first).

Consulting 120

Consulting Machine Learning Data Science Data Pipeline 120