Monte Carlo

SEPTEMBER 12, 2022

This new approach empowers business users to access and act on their data, while reinforcing the data warehouse as the source of truth. Compared to software engineering, Maxime says, “I think the on-ramp for people to become more sophisticated with data is just easier and more accessible to more people.”

BI 52

BI Data Governance ETL Tools Data Warehouse 52

Data Engineering Podcast

NOVEMBER 9, 2020

He also shares the internal architecture, how he approached the design to make it accessible and easy to use, and how it autodiscovers the schemas and metadata for your source systems. Are you bogged down by having to manually manage data access controls, repeatedly move and copy data, and create audit reports to prove compliance?

Building 100

Building PostgreSQL BI Metadata 100

AltexSoft

AUGUST 29, 2023

Such an object storage model allows metadata tagging and incorporating unique identifiers, streamlining data retrieval and enhancing performance. Data storage and processing The data storage and processing layer is where the ingested data resides and undergoes transformations to make it more accessible and valuable for analysis.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

AUGUST 31, 2021

While this “data tsunami” may pose a new set of challenges, it also opens up opportunities for a wide variety of high value business intelligence (BI) and other analytics use cases that most companies are eager to deploy. . Consideration of both data & metadata in the migration. All rights reserved. Value Achieved.

Data Warehouse 81

Data Warehouse Database-centric Metadata Cloud 81

Monte Carlo

JUNE 28, 2022

By design, data was less structured with limited metadata and no ACID properties. Unity Catalog The Unity Catalog unifies metastores, catalogs, and metadata within Databricks. The Databricks Unity Catalog does what it says: it unifies individual metastores, catalogs and serves as a central metadata repository in Databricks.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Monte Carlo

MARCH 16, 2023

Today, nearly a decade later, Randy leads over 20 people on the Best Egg data and BI teams. The analytics users across the company access most data through Snowflake and PowerBI. As a startup, Best Egg had been focused on proving its business model, not establishing organization-wide data governance.

Software Engineer 52

Software Engineer Software Engineering Data Governance Government 52

ProjectPro

FEBRUARY 16, 2023

Many companies use AWS , including government agencies and multimillion-dollar startups. Security AWS offers various security features companies can use to protect their data, such as encryption, access controls, and network isolation. AWS Glue has a central metadata repository called the Glue catalog.

AWS 52

AWS Data Management ETL Tools Management 52

Monte Carlo

JULY 10, 2023

For example, let’s say a streaming provider has 10 million overall subscribers who can access its content. Data profiling Data profiling uses a tool or programming language to surface metadata about your data. Accuracy reflects the degree to which the data correctly describes the “real-world” objects being described.

Data Collection 40

Data Collection Data Governance Government Data 40

Monte Carlo

MARCH 16, 2023

Today, nearly a decade later, Randy leads over 20 people on the Best Egg data and BI teams. The analytics users across the company access most data through Snowflake and PowerBI. As a startup, Best Egg had been focused on proving its business model, not establishing organization-wide data governance.

Software Engineer 40

Software Engineer Software Engineering Data Governance Government 40

dbt Developer Hub

JULY 2, 2023

Agile development ​ dbt Cloud includes built-in Git with accessible features directly from its IDE, which simplifies development immensely. Apart from data modelling work, you need to agree on naming conventions, hash algorithm, staging strategy, and data types for standard metadata attributes, and make sure these are all well documented.

Cloud 52

Cloud Data Warehouse Data BI 52

Monte Carlo

APRIL 16, 2022

For large companies where data quality is paramount, this process involves a manual, intensive governance framework with a tight coupling between data engineers and the data architects embedded across different domains in order to leverage data quickly for operational insights. Many businesses still operate this way today.

Data Warehouse 52

Data Warehouse Architecture Data Government 52

Cloudera

AUGUST 30, 2018

Cloud service architecture – storing and accessing data and services over the Internet instead of your data center or local computer’s hard drive. How do I meet a growing demand for self-serve BI, while not exploding my data warehouse budgets? How do I get to the next level in the data-driven journey fast enough?

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40

Monte Carlo

APRIL 7, 2021

As the PM for Protocols , our data governance tool, I spent a lot of time thinking about and building dashboards to evaluate the quality of data our customers were sending to Segment. Your data lineage should include data products like BI reports, ML models or reverse ETL sinks to be useful. Field-level lineage is a plus.

Data Engineering 40

Data Engineering Data Engineer Engineering Datasets 40

Data Engineering Podcast

NOVEMBER 26, 2023

Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. Support Data Engineering Podcast Summary Building a data platform that is enjoyable and accessible for all of its end users is a substantial challenge. Go to [materialize.com]([link] today and get 2 weeks free!

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Monte Carlo

FEBRUARY 26, 2024

It uses metadata to create a picture of the data, as well as the relationships between data assets of diverse sources, and the processing that takes place as data moves through systems. Additionally, data catalogs can centrally enforce rules of access, security, and governance, all in a way that is both automatic and visible.

Metadata 52

Metadata Government Data Data Governance 52

Cloudera

FEBRUARY 22, 2022

Through our contributions, we have extended support for Hive and Impala, delivering on the vision of a data architecture for multi-function analytics from large scale data engineering (DE) workloads to fast BI and querying (within DW) and machine learning (ML). Separation of physical and logical layout: Iceberg supports hidden partitioning.

Metadata 109

Metadata Datasets BI SQL 109

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Data quality issues deter trust and hinder accurate analytics. Modern data architectures.

Data Architecture 78

Data Architecture Architecture Data Lake NoSQL 78

Cloudera

MARCH 23, 2022

Apache Iceberg is a high-performance, open table format, born-in-the cloud that scales to petabytes independent of the underlying storage layer and the access engine layer. For query planning Iceberg relies on metadata files, as mentioned earlier, that contains where the data lives and how partitioning and schema are spread across the files.

Metadata 90

Metadata Data Architecture BI Machine Learning 90

DataKitchen

FEBRUARY 2, 2023

We’ve read many predictions for 2023 in the data field: they cover excellent topics like data mesh, observability, governance, lakehouses, LLMs, etc. This will drive a new consolidated set of tools the data team will leverage to help them govern, manage risk, and increase team productivity. What will exist at the end of 2025?

Metadata 52

Metadata BI Government ETL Tools 52

Cloudera

JANUARY 21, 2021

You already know that a distributed environment is much tougher for your company to manage, secure, and govern. The ability to give LoB users quick access to self-service data warehousing, while ensuring compliance, is the main reason top Financial Services organizations like DBS Bank and others have selected CDW over point solutions.

IT 93

IT Data Lake Data Warehouse Cloud Storage 93

Cloudera

FEBRUARY 11, 2019

The root cause is firmly entrenched in legacy systems and traditional data governance challenges that not only result in data silos but also the misguided belief that data privacy is diametrically opposed to effective exploration of information. Governing digital transformation. Governing digital transformation.

Government 57

Government Data Governance Data Science Machine Learning 57

Monte Carlo

NOVEMBER 6, 2023

They can range in terms of complexity, ease of use, and feature sets, but all are designed to help illuminate the dark corners of your data repositories, and are a critical component of your data governance practice. It offers a 360-degree view of your data, including data lineage, relationships, and rich metadata.

Metadata 40

Metadata Unstructured Data Government Data Governance 40

Towards Data Science

MAY 19, 2023

Business users are unable to find and access data assets critical to their workflows. Tech Target , defines a data silo as a repository of data controlled by one department or business unit and, therefore, not wholly or easily accessible by other departments within the same organisation. Do any of the below scenarios seem familiar?

Pipeline-centric 104

Pipeline-centric Data Software Engineer Software Engineering 104

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Well, the connective tissue that powers and integrates these services is frequently found in the metadata of table formats (storage) and query/job logs (compute).

Metadata 95

Metadata Data Warehouse Data Lake Data Science 95

Monte Carlo

AUGUST 30, 2023

You will also need to securely store and provide dbt with the necessary credentials to access your target database. Make sure logs are accessible for future reference. Also, remember data governance. Does dbt testing cover all your governance bases? With pipelines, the environment starts clean every time.

SQL 52

SQL Datasets Database High Quality Data 52

Cloudera

JUNE 30, 2022

With Shared Data Experience (SDX) which is built in to CDP right from the beginning, customers benefit from a common metadata, security, and governance model across all their data. . Customers use a metadata-only migration in a single command, without touching any of the underlying large data sets.

Data Lake 87

Data Lake Business Intelligence Metadata Data Warehouse 87

Snowflake

MAY 22, 2023

Cross-Cloud Snowgrid Account Replication expands replication beyond databases – general availability Account Replication, now generally available, expands replication beyond databases to account metadata and integrations, making business continuity truly turnkey. Learn more here. Learn more.

Healthcare 52

Healthcare Scala Medical Transportation 52

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Tableau – Often referred to as a leader in the BI industry, it has an easy-to-use interface.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

SEPTEMBER 9, 2022

Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. These new formats need to accommodate the massive scale increases while shortening the response windows for accessing, analyzing, and using these data sets for business insights. According to Gartner, Inc.

Architecture 101

Architecture Metadata Unstructured Data Machine Learning 101

Snowflake

FEBRUARY 29, 2024

While latitude and longitude columns can often be used by BI tools and Python libraries to plot points on a map, or shade common administrative boundaries such as states, provinces and countries, companies can do so much more with this valuable geospatial data to perform complex analyses. We hear you, world. What is H3?

Insurance 84

Insurance SQL BI Consulting 84

AltexSoft

NOVEMBER 10, 2021

At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store. Issues with data security and governance. Schema enforcement and data governance. Poor data quality, reliability, and integrity. ACID transaction support.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

NOVEMBER 23, 2021

To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization. In simple terms, data remains in original sources while users can access and analyze it virtually via special middleware. Real-time access.

Process 69

Process Data Lake Metadata Data Warehouse 69

Monte Carlo

AUGUST 25, 2023

A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor. For metadata organization, they often use Hive, Amazon Glue, or Databricks. One advantage of data warehouses is their integrated nature. Or maybe both.)

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

SEPTEMBER 23, 2021

Data lineage provides the answer by telling you which upstream sources and downstream ingestors were impacted, as well as which teams are generating the data and who is accessing it. Full-stack coverage from ingestion to the BI layer Full-stack coverage is necessary to fully understand data health. Image courtesy of Monte Carlo.

BI 52

BI Data Metadata Data Pipeline 52

Monte Carlo

MAY 31, 2022

Metadata from the data warehouse/lake and from the BI tool of record can then be used to map the dependencies between the tables and dashboards. Spark lineage is the metadata detailing the journey data takes across its lifecycle including source, creator, transformations, and related data sets. It’s a really elegant solution….here’s

Data Lake 52

Data Lake Building Scala Metadata 52

Monte Carlo

AUGUST 10, 2023

Data lineage provides the answer by telling you which upstream sources and downstream ingestors were impacted, as well as which teams are generating the data and who is accessing it. Data pipeline observability involves using machine learning to monitor the metadata of pipelines to for anomalies in data freshness, volume, and schema.

Data Pipeline 98

Data Pipeline Software Engineer Software Engineering Machine Learning 98

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. What happens, when a data scientist, BI developer , or data engineer feeds a huge file to Hadoop?

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59