erwin

FEBRUARY 13, 2020

The numerous data types and data sources that exist today weren’t designed to work together, and data infrastructures have been cobbled together over time with disparate technologies, poor documentation and little thought for downstream integration. Finding metadata, “the data about the data,” isn’t easy.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Cost-Benefit 78

Cost-Benefit Data Warehouse Optimization Unstructured Data 78

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 84

Enterprise Data Warehouse Snapshot Cost-Benefit 84

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

erwin

MARCH 8, 2019

Therefore, the organization needed to catalog the data it acquires from suppliers, ensure its quality, classify it, and then sell it to customers. The company wanted to assemble the data in a data warehouse and then provide controlled access to it. This, among other safeguards, ensures data quality.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

Alation

FEBRUARY 7, 2023

It wouldn’t be until 2013 that the topic of data lineage would surface again – this time while working on a data warehouse project. Data warehouses obfuscate data’s origin In 2013, I was a Business Intelligence Engineer at a financial services company. What’s the right lineage level? It depends!

Metadata 52

Metadata Data Warehouse Visualization Data Quality 52

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

Jet Global

MAY 1, 2020

The mechanical solution is to build a data warehouse. This will be the place where everybody has come together and agreed upon the data that you are going to use to manage your business, and how that data is going to be combined with which methods you’re going to use to calculate things like gross profit and net income.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

IT 317

IT Statistics KPI Data-driven 317

erwin

JANUARY 11, 2019

A company can’t effectively implement data governance – documenting and applying business rules and processes, analyzing the impact of changes and conducting audits – if it fails at data management. The problem usually starts by relying on manual integration methods for data preparation and mapping.

Data Governance 40

Data Governance Risk Metadata Management 40

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 75

Data Quality Data Lake Data-driven Metrics 75

Alation

SEPTEMBER 7, 2021

In the next section, let’s take a deeper look into how these key attributes help data scientists and analysts make faster, more informed decisions, while supporting stewards in their quest to scale governance policies on the Data Cloud easily. Find Trusted Data. Verifying quality is time consuming. Two problems arise.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

Ontotext

MARCH 18, 2020

The many data warehouse systems designed in the last 30 years present significant difficulties in that respect. When designing a system’s architecture, it’s impossible to know from the start all the ways data will be used. The third challenge is how to combine data management with analytics.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Ontotext

MARCH 8, 2023

However, this information is typically stored in disparate locations, often hidden within departmental documents or applications. As such, most large financial organizations have moved their data to a data lake or a data warehouse to understand and manage financial risk in one place.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Alation

FEBRUARY 13, 2020

Important evaluation features include capabilities to preview a dataset, see all associated metadata, see user ratings, read user reviews and curator annotations, and view data quality information. Figure 2 illustrates how analysis processes change when analysts work with a data catalog.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

erwin

FEBRUARY 19, 2021

A strong data management strategy and supporting technology enables the data quality the business requires, including data cataloging (integration of data sets from various sources), mapping, versioning, business rules and glossaries maintenance and metadata management (associations and lineage).

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

Cloudera

AUGUST 30, 2022

It outlines a scenario in which “recently married people might want to change their names on their driver’s licenses or other documentation. That should be easy, but when agencies don’t share data or applications, they don’t have a unified view of people. Data quality issues deter trust and hinder accurate analytics.

Data Architecture 78

Data Architecture Data Lake Metadata Data Warehouse 78

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 99

Data Lake Data Warehouse Management Risk 99

Alation

JULY 19, 2022

For example, a new data scientist who is curious about which customers are most likely to be repeat buyers, might search for customer data only to discover an article documenting a previous project that answered their exact question. Modern data catalogs also facilitate data quality checks.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. The central concept is the idea of a document.

Metadata 95

Metadata Visualization Unstructured Data Data mining 95

Cloudera

APRIL 14, 2021

Precisely Data Integration, Change Data Capture and Data Quality tools support CDP Public Cloud as well as CDP Private Cloud. Data pipelines that are bursty in nature can leverage the public cloud CDE service while longer running persistent loads can run on-prem.

Data Warehouse 83

Data Warehouse Data Processing Data Quality Machine Learning 83

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. Purchase date represents one customer touch point.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

Cost-Benefit 80

Cost-Benefit Metadata Data Governance Modeling 80

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Domino Data Lab

JUNE 15, 2021

At a certain point, as the demand keeps growing, the data volumes rapidly increase. Data is no longer stored in CSV files, but in a dedicated, purpose built data lake / data warehouse. Existing preprocessing, data ingestion, and data quality processes can be converted from Java/Spark into Java UDFs.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

BI-Survey

FEBRUARY 23, 2023

Concerns about data security should be taken seriously, but must not block a transformation to data access that is open in principle and has as few hurdles as possible. Better data access demands data knowledge Knowledge about data creates transparency and helps people to find, understand, evaluate and use data.

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

datapine

AUGUST 29, 2022

Best for: the seasoned BI professional who is ready to think deep and hard about important issues in data analytics and big data. An excerpt from a rave review: “…a tour de force of the data warehouse and business intelligence landscape.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

datapine

FEBRUARY 22, 2022

They can govern the implementation with a documented business case and be responsible for changes in scope. On the flip side, document everything that isn’t working. What data analysis questions are you unable to currently answer? This should also include creating a plan for data storage services. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

CIO Business Intelligence

NOVEMBER 7, 2023

Centralized reporting boosts data value For more than a decade, pediatric health system Phoenix Children’s has operated a data warehouse containing more than 120 separate data systems, providing the ability to connect data from disparate systems. Companies should also incorporate data discovery, Higginson says.

Data Warehouse 141

Data Warehouse Digital Transformation Reporting Data-driven 141

Alation

AUGUST 4, 2022

“File-based storage of data is the norm even under more relational models. [In In the cloud], Graph databases, document stores, file stores, relational stores all now exist, each addressing different challenges.” In this way, the cloud has democratized access to some of the best outputs of big data.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. This is where SAP Datasphere (the next generation of SAP Data Warehouse Cloud) comes in.

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Cloudera

AUGUST 26, 2020

The Cloudera Connect Technology Certification program uses a well-documented process to test and certify our Independent Software Vendors’ (ISVs) integrations with our data platform. This allows our customers to reduce spend on highly specialized hardware and leverage the tools of a modern data warehouse. .

Machine Learning 83

Machine Learning Big Data Data Warehouse Data-driven 83

AWS Big Data

APRIL 25, 2023

The following factors guided our decision: Tool close to data – It was important to have the data visualization tool as close to the data as possible. At Dafiti, the entire infrastructure is on AWS, and we use Amazon Redshift as our Data Warehouse. Conclusion Choosing a data visualization tool is not a simple task.

Visualization 52

Visualization IT Data-driven Reporting 52