Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Alation

MARCH 21, 2023

Why is data analytics important for travel organizations? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. They may also suffer from data duplication, which undermines their analytics models.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

MARCH 1, 2023

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. The workflow begins with an AWS Glue job that converts the CSV files into Apache Parquet data format.

Data Lake 87

Data Lake Deep Learning Modeling Interactive 87

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

MAY 1, 2024

Excel-based data utilization Microsoft Excel is available on almost everyone’s PC in the company, and it helps lower the hurdles when starting to utilize data. However, Excel is mainly designed for spreadsheets; it’s not designed for large-scale data analytics and automation.

Dashboards 113

Dashboards Data-driven Publishing Cost-Benefit 113

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 60

Data Architecture Data Lake Machine Learning Data Governance 60

Alation

AUGUST 4, 2022

Aligning business goals to data usage is a key foundation. There is no digital transformation without business-aligned data control,” Capgemini Executive Steve Jones adds. “The architectural model of big data is fundamental to this.”. Everything comes down to what organizations do with data.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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 123

Unstructured Data Data-driven Visualization Data Quality 123

AWS Big Data

JULY 13, 2023

To reflect the needs of their customers spread across different geographies and industries, Altron has organized their operating model across individual Operating Companies (OpCos). Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

Optimization 92

Optimization B2B Data Quality Sales 92

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. After all, Alex may not be aware of all the data available to her.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. About the authors Basheer Sheriff is a Senior Solutions Architect at AWS.

Analytics 98

Analytics IT Data Lake Visualization 98

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

IBM Big Data Hub

APRIL 27, 2022

Since its uniquely metadata-driven, the abstraction layer of a data fabric makes it easier to model, integrate and query any data sources, build data pipelines, and integrate data in real-time. Data fabric vs data mesh: How does a data fabric relate to a data mesh?

Management 81

Management Metadata Data Architecture Data Lake 81

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 82

Insurance Data Lake Data-driven Management 82

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 78

Cost-Benefit Metadata Data Governance Modeling 78

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 96

Analytics Key Performance Indicator Data Warehouse Data-driven 96

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.

Analytics 55

Analytics Data Lake Testing Optimization 55

Alation

JANUARY 27, 2022

How do businesses transform raw data into competitive insights? Data analytics. Modern businesses are increasingly leveraging analytics for a range of use cases. Analytics can help a business improve customer relationships, optimize advertising campaigns, develop new products, and much more. What is Data Analytics?

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

DataKitchen

OCTOBER 11, 2021

The biggest challenge is broken data pipelines due to highly manual processes. Figure 1 shows a manually executed data analytics pipeline. First, a business analyst consolidates data from some public websites, an SFTP server and some downloaded email attachments, all into Excel. Adding Tests to Reduce Stress.

Testing 152

Testing Metadata Dashboards Statistics 152

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 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 107

Data Warehouse Testing Data Quality Reporting 107

AWS Big Data

MARCH 3, 2023

Finally, data integrity is of paramount importance. Every event in the data source can be relevant, and our customers don’t tolerate data loss, poor data quality, or discrepancies between the source and Tricentis Analytics.

Software 52

Software Data Lake Testing Cost-Benefit 52

Ontotext

FEBRUARY 26, 2024

However, it still requires more effort than building a single-purpose graph, like a labeled property graph (LPG), where you can whiteboard your graph model in an hour. Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. RDF vs LPG?

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

AWS Big Data

JULY 12, 2023

With a wide array of data sources, including transactional databases, log files, and event streams, you need a simple-to-use solution capable of efficiently ingesting and transforming large volumes of data in real time, ensuring data cleanliness, structural integrity, and data team collaboration.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

IBM Big Data Hub

DECEMBER 7, 2023

C-OLAP optimized data storage for faster query processing, while IM-OLAP stored data in memory to minimize data access latency and enable real-time analytics. Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses.

OLAP 59

OLAP Slice and Dice Cost-Benefit Data Warehouse 59

Andrew White

JANUARY 11, 2021

Where does the Data Architect role fits in the Operational Model ? Assuming a data architect helps model and guide and assist D&A then they play a key role. Note: Delivery of data, analytics solutions and the sustainment of technology, data and services is a question. Governance. Architecture.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

datapine

APRIL 15, 2020

To look into these processes in more detail, we will now explain the agile BI methodology as well as for analytics and provide steps for agile BI development. Agile Business Intelligence & Analytics Methodology. In the traditional model communication between developers and business users is not a priority.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 77

Cost-Benefit Metadata Optimization Management 77

Cloudera

AUGUST 4, 2021

And if data security tops IT concerns, data governance should be their second priority. Not only is it critical to protect data, but data governance is also the foundation for data-driven businesses and maximizing value from data analytics. Security: It must serve data throughout a system.

Data Governance 85

Data Governance Metadata Data-driven Enterprise 85

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

Andrew White

MARCH 22, 2019

I jest here; what I mean to say is that economics and rational, smart models should trump perfectly designed ideas. This ties into the failure of data governance and MDM (see first item in this list). This ties into the failure of data governance and MDM (see first item in this list). Economics over architecture.

Analytics 68

Analytics Metadata Data Governance Management 68