CIO Business Intelligence

SEPTEMBER 20, 2023

On the agribusiness side we source, purchase, and process agricultural commodities and offer a diverse portfolio of products including grains, soybean meal, blended feed ingredients, and top-quality oils for the food industry to add value to the commodities our customers desire. The data can also help us enrich our commodity products.

Data Lake 135

Data Lake Data-driven Dashboards Risk 135

Ontotext

APRIL 10, 2024

Data ecosystems have become jungles and in spite of all the technology, data teams are struggling to create a modern data experience. Drowning in Data, Thirsting for Context We’ve heard the saying, “Data, data everywhere. ” As more data accumulates, context gets diluted and lost.

Metadata 52

Metadata Data Lake Data Warehouse Data Quality 52

AWS Big Data

DECEMBER 13, 2023

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. Data quality check – The data quality module enables you to perform quality checks on a huge amount of data and generate reports that describe and validate the data quality.

Metadata 86

Metadata Data Lake Visualization Data Transformation 86

DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. Ensuring that data is available, secure, correct, and fit for purpose is neither simple nor cheap.

Consulting 244

Consulting Testing Data Lake Data Quality 244

IBM Big Data Hub

JUNE 8, 2022

Implementing the right data strategy spurs innovation and outstanding business outcomes by recognizing data as a critical asset that provides insights for better and more informed decision-making. By taking advantage of data, enterprises can shape business decisions, minimize risk for stakeholders, and gain competitive advantage.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

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 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. But first, let’s define the data mesh design pattern. The past decades of enterprise data platform architectures can be summarized in 69 words.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

CIO Business Intelligence

APRIL 1, 2024

GenAI requires high-quality data. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key. 2024 2 The State of Generative AI in the Enterprise, Deloitte, Jan.

Data Lake 142

Data Lake Consulting Uncertainty Risk 142

CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

Finance 140

Finance Management Metadata Data Quality 140

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.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Ontotext

MARCH 8, 2023

Use Case #1: Customer 360 / Enterprise 360 Customer data is typically spread across multiple applications, departments, and regions. Each team and system need to keep diverse sets of data about their customers in order to play their specific role – inadvertently leading to siloed experiences.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

APRIL 4, 2024

Many enterprises are migrating their on-premises data stores to the AWS Cloud. During data migration, a key requirement is to validate all the data that has been moved from source to target. This data validation is a critical step, and if not done correctly, may result in the failure of the entire project.

Data Quality 61

Data Quality Data Lake Data Warehouse Data-driven 61

Ontotext

FEBRUARY 12, 2024

As discussed in part one, the data mesh paradigm is still a relatively new concept with implementations in the early stages. Most enterprises have years of legacy systems, processes, and practices that make it more demanding to quickly jump onto the data mesh bandwagon. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Timo Elliott

DECEMBER 14, 2022

Gartner calls it the Composable Enterprise , for example – it’s about having a solid information foundation that enables fast and flexible creation of what they call composable applications that allow you to create new applications and workflows by just bringing together modular components. Business Process. Business Context.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

CIO Business Intelligence

APRIL 24, 2024

It’s universally accepted that to thrive, enterprises must embrace transformation through technology. The goal is to correlate all types of data that affect assets and bring it all into the digital twin to take timely action,” says D’Accolti.

Digital Transformation 105

Digital Transformation Business Intelligence Unstructured Data Data Lake 105

CIO Business Intelligence

MARCH 18, 2024

For a typical project that will likely involve a Snowflake data lake hosted currently on Azure, Menon stresses that quality of data is critical. “AI AI tools rely on the data in use in these solutions. Good data management practices will be needed to get the desired results and AI solutions,” she says.

Risk 133

Risk Cost-Benefit Data Processing Testing 133

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

Timo Elliott

JANUARY 3, 2022

It’s stored in corporate data warehouses, data lakes, and a myriad of other locations – and while some of it is put to good use, it’s estimated that around 73% of this data remains unexplored. Improving data quality. Unexamined and unused data is often of poor quality. Data augmentation.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

Cloudera

DECEMBER 1, 2022

RI is a global leader in the design and deployment of large-scale, production-level modern data platforms for the world’s largest enterprises. Luke: Observability has been around for a while as a term in DevOps circles, but what is data observability? Monitoring volume provides another data quality checkpoint.

Metrics 80

Metrics Data Quality Data Lake Statistics 80

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Ontotext

NOVEMBER 16, 2023

Clarifying what data mesh is and how it works is important, but even more so is starting with the why. Why Organizations Need A Data Mesh The data mesh paradigm aims to address some of the biggest pain points for most organizations. This becomes particularly problematic when dealing with veracity of data.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake.

Data Warehouse 102

Data Warehouse Testing Data Quality Reporting 102

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

Data Governance 145

Data Governance IT Risk Data Lake 145

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 Data Quality Metadata Data Governance 52

AWS Big Data

JANUARY 30, 2023

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities.

Insurance 77

Insurance Data Lake Data-driven Management 77

DataKitchen

NOVEMBER 18, 2022

In addition to the tracking of relationships and quality metrics, DataOps Observability journeys allow users to establish baselines?concrete concrete expectations for run schedules, run durations, data quality, and upstream and downstream dependencies. And she’ll know when newer data will arrive.

Testing 130

Testing Statistics Measurement Metrics 130

CIO Business Intelligence

MARCH 27, 2024

“La qualità del dato viene ottenuta definendo un processo che coinvolge tutti gli attori aziendali e gli strumenti di misurazione appositi”, evidenzia Francesco Saverio Colasuonno, Data & Analytics Office Manager di INAIL. “Le Ma ci aspettiamo di estenderla ad altri use-case”.

Data Governance 52

Data Governance Data Lake Data Strategy Data-driven 52

bridgei2i

MARCH 11, 2021

With improved data cataloging functionality, their systems can become responsive. It’ll become easier to store metadata (data lakes, warehouses, data quality systems, etc.) Over time, as more data is constantly fed to the responsive system, ML algorithms improve their efficiency. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 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

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

Alation

NOVEMBER 28, 2022

Spreadsheet users can now pull high-quality data, with a view into its context and history, directly from Alation into Google Sheets. Talo: They say spreadsheets are “the dark matter” of the enterprise. Krishna: Spreadsheets are truly the dark matter of the data universe. What problems do spreadsheets create?

Metadata 52

Metadata Enterprise Cost-Benefit Finance 52

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. But the attempts to standardize data across the entire enterprise haven’t produced the desired results.

Data Governance 40

Data Governance Risk Metadata Management 40

Jedox

OCTOBER 22, 2020

Gartner defines “dark data” as the data organizations collect, process, and store during regular business activities, but doesn’t use any further. Gartner also estimates 80% of all data is “dark”, while 93% of unstructured data is “dark.”. Limited self-service reporting across the enterprise. Drill-down capability.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

Alation

NOVEMBER 2, 2022

“It went from being really focused on data catalogs to becoming a much broader data intelligence platform – and one that’s cloud-native and therefore relevant for a much broader set of users within an enterprise, not just analysts or stewards, but all the way down to business users. We really like that ambition.

Data Governance 98

Data Governance Marketing Finance Data Lake 98

Alation

MARCH 22, 2022

As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT. Simply put, IDF standardizes data engineering processes. DataOps has emerged as an exciting solution.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 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