AWS Big Data

APRIL 4, 2024

Griffin is an open source data quality solution for big data, which supports both batch and streaming mode. In today’s data-driven landscape, where organizations deal with petabytes of data, the need for automated data validation frameworks has become increasingly critical.

Data Quality 64

Data Quality Data Lake Data Warehouse Data-driven 64

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. Easy to report problems and receive updates on fixes.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

APRIL 24, 2024

We started with an evolution of the CRM to manage the citizen relationship, and the various requests and reports: those who come into contact with the AMA must be recognized on any channel and receive consistent answers in a multichannel perspective,” he says. From there, the actual digitization project can be implemented. “We

Digital Transformation 105

Digital Transformation Business Intelligence Unstructured Data Data Lake 105

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. Another complication was the existing data silos.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

DataKitchen

NOVEMBER 18, 2022

So, the only way for a data journey to truly observe what’s happening is to get his tools and pipelines to auto-report events. An effective DataOps observability solution requires supporting infrastructure for the journeys to observe and report what’s happening across your data estate.

Testing 130

Testing Statistics Measurement Metrics 130

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

AWS Big Data

NOVEMBER 9, 2023

As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform. Flat files – Other systems supply data in the form of flat files of different formats. Data ingestion Data from various sources are grouped into two major categories: real-time ingestion and batch ingestion.

Data Warehouse 108

Data Warehouse Testing Data Quality Reporting 108

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Metadata Data Quality Data Governance 52

IBM Big Data Hub

JUNE 8, 2022

However, a foundational step in evolving into a data-driven organization requires trusted, readily available, and easily accessible data for users within the organization; thus, an effective data governance program is key. Here are a few common data management challenges: Regulatory compliance on data use.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Ensuring data quality is made easier as a result.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. It consists of full-day and intraday tables.

Analytics 56

Analytics Data Lake Testing Optimization 56

Jedox

OCTOBER 22, 2020

Other challenges to data analytics include data storage, data quality, and a lack of knowledge and tools necessary to make sense of the data and generate those critical insights. Limited self-service reporting across the enterprise. Self-service reporting. Exception reporting.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

FineReport

MARCH 24, 2024

The primary objective of a data analyst is to transform raw data into meaningful insights that drive organizational improvements. By conducting extensive research and analysis, they generate reports that inform strategic decisions, identify areas for enhancement, and guide the implementation of new initiatives.

Statistics 52

Statistics Data mining Visualization Reporting 52

CIO Business Intelligence

MARCH 27, 2024

Le aziende italiane investono in infrastrutture, software e servizi per la gestione e l’analisi dei dati (+18% nel 2023, pari a 2,85 miliardi di euro, secondo l’Osservatorio Big Data & Business Analytics della School of Management del Politecnico di Milano), ma quante sono giunte alla data maturity?

Data Governance 52

Data Governance Data Lake Data Strategy Data-driven 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

bridgei2i

MARCH 11, 2021

They have access to large amounts of data. But, the data comes from distinct sources and systems. For instance, a small business owner who does all accounting work on Excel and uses another system to send reports will have two distinct data sources to focus on. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

CIO Business Intelligence

JANUARY 30, 2024

Corporate ESG reporting is getting real for companies around the globe. Enacted and proposed regulations in the EU, US, and beyond are deepening reporting requirements in an effort to change business behavior. The foundation for ESG reporting, of course, is data. The foundation for ESG reporting, of course, is data.

Reporting 115

Reporting Data Quality Strategy Data-driven 115

Alation

JANUARY 26, 2023

It’s equally important that they know the reporting structure. Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Make sure that the value of data increases over time.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. Many organizations have built a data lake to solve their data storage, access, and utilization challenges.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Alation

JUNE 14, 2021

Intelligent systems powered by machine learning are necessary for overcoming the challenges of data management. According to a 2020 451 Research report , “data catalogs are rapidly building out automated functionality,” including “automated suggestions, automated discovery and tagging, and automated data-quality scoring.”

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

erwin

JANUARY 11, 2019

It’s only when companies take their first stab at manually cataloging and documenting operational systems, processes and the associated data, both at rest and in motion, that they realize how time-consuming the entire data prepping and mapping effort is, and why that work is sure to be compounded by human error and data quality issues.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

Ontotext

MARCH 8, 2023

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. Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

DataKitchen

DECEMBER 9, 2022

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making. By using DataOps, organizations can improve. Query> When do DataOps?

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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 102

Data Lake Data Warehouse Management Risk 102

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. On the other hand, they don’t support transactions or enforce data quality.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders. Athena exposes the content of the reporting zone for consumption.

Optimization 91

Optimization B2B Data Quality Sales 91

Cloudera

MARCH 28, 2024

Among the most common challenges to achieving AI adoption at scale were data quality and availability (36%), scalability and deployment (36%), integration with existing systems and processes (35%), and change management and organizational culture (34%).

Data Architecture 89

Data Architecture Strategy Data Lake Data-driven 89

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

AWS Big Data

MARCH 26, 2024

Without C360, businesses face missed opportunities, inaccurate reports, and disjointed customer experiences, leading to customer churn. AWS provides different services for building data ingestion pipelines: AWS Glue is a serverless data integration service that ingests data in batches from on-premises databases and data stores in the cloud.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

DataKitchen

OCTOBER 11, 2021

The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. The automated orchestration published the data to an AWS S3 Data Lake. I use the business rules I received from the business analyst to process the source data using Python.

Testing 152

Testing Metadata Dashboards Statistics 152

datapine

APRIL 15, 2020

It’s necessary to say that these processes are recurrent and require continuous evolution of reports, online data visualization , dashboards, and new functionalities to adapt current processes and develop new ones. Discover the available data sources. Collaboratively develop reports.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

BizAcuity

APRIL 1, 2023

Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture. Without a strong BI infrastructure, it can be difficult to effectively collect, store, and analyze data.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

Several large organizations have faltered on different stages of BI implementation, from poor data quality to the inability to scale due to larger volumes of data and extremely complex BI architecture. Without a strong BI infrastructure, it can be difficult to effectively collect, store, and analyze data.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Quality is job one.

Unstructured Data 130

Unstructured Data Data-driven Visualization Data Quality 130

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Only metadata will be regenerated. Metadata management .

Metadata 76

Metadata Data Warehouse Snapshot Data Quality 76