IBM Big Data Hub

APRIL 25, 2023

We also made the case that query and reporting, provided by big data engines such as Presto, need to work with the Spark infrastructure framework to support advanced analytics and complex enterprise data decision-making. What can enterprises do different from what they are already doing today?

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

Cloudera

FEBRUARY 7, 2019

A key pillar in the transformation journey is focused on robust data operations that can help ATB deliver timely, relevant and delightful service. The company sought a data management platform that would allow its enterprise to handle greater data variety, velocity and volume in a cost-effective manner.

Big Data 63

Big Data Data Analytics Analytics Data Architecture 63

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 91

Data Governance Unstructured Data Metadata Data Lake 91

AWS Big Data

APRIL 10, 2024

and zero-ETL support) as the source, and a Redshift data warehouse as the target. The integration replicates data from the source database into the target data warehouse. Additionally, you can choose the capacity, to limit the compute resources of the data warehouse. For this post, set this to 8 RPUs.

Data Warehouse 88

Data Warehouse Analytics Metrics Snapshot 88

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

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 91

Data Lake Data Warehouse Machine Learning Cost-Benefit 91

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

AWS Big Data

NOVEMBER 17, 2023

Amazon Redshift is a cloud data warehousing service that provides high-performance analytical processing based on a massively parallel processing (MPP) architecture. Building and maintaining data pipelines is a common challenge for all enterprises. These SCDs identify how a row in a table changes over time.

Snapshot 87

Snapshot Data Processing Testing Data Warehouse 87

CIO Business Intelligence

SEPTEMBER 14, 2023

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas.

Analytics 134

Analytics Data Science Unstructured Data Data mining 134

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Overall data architecture and strategy. Use case priority and workload identifications.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

Jen Stirrup

MAY 3, 2020

Azure Synapse is an Azure-based cloud analytics service that provides insights on all data across data warehouses and big data analytics systems. It combines familiar SQL technologies such as data warehousing with Spark technologies used in big data analytics.

Big Data 56

Big Data Data Warehouse Machine Learning Business Intelligence 56

Ontotext

AUGUST 22, 2023

The age of Big Data inevitably brought computationally intensive problems to the enterprise. Central to today’s efficient business operations are the activities of data capturing and storage, search, sharing, and data analytics. How to Get a Semantic Edge?

Metadata 52

Metadata Knowledge Discovery Big Data Enterprise 52

AWS Big Data

FEBRUARY 1, 2024

This stack creates the following resources and necessary permissions to integrate the services: Data stream – With Amazon Kinesis Data Streams , you can send data from your streaming source to a data stream to ingest the data into a Redshift data warehouse. version cluster. version cluster.

Data Warehouse 120

Data Warehouse Dashboards Risk Management Risk 120

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective. Check out this list below to see some of them in action: Comcast.

Enterprise 47

Enterprise Data Lake Data mining IoT 47

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 60

Data Quality Data Lake Data Warehouse Data-driven 60

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 89

Data Warehouse Data-driven Machine Learning B2B 89

IBM Big Data Hub

JANUARY 5, 2023

Ill-timed business decisions and misinformed business processes, missed revenue opportunities, failed business initiatives and complex data systems can all stem from data quality issues. Several factors determine the quality of your enterprise data like accuracy, completeness, consistency, to name a few.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 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. Prantik specializes in architecting modern data and analytics platforms in AWS.

Data Warehouse 101

Data Warehouse Testing Data Quality Reporting 101

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 95

Data Warehouse Testing Data Lake Data-driven 95

CIO Business Intelligence

AUGUST 9, 2022

Database-centric: In larger organizations, where managing the flow of data is a full-time job, data engineers focus on analytics databases. Database-centric data engineers work with data warehouses across multiple databases and are responsible for developing table schemas. Data engineer job description.

Analytics 128

Analytics Data Science Statistics Unstructured Data 128

IBM Big Data Hub

NOVEMBER 3, 2023

It allows your business to ingest continuous data streams as they happen and bring them to the forefront for analysis, enabling you to keep up with constant changes. However, not all of it is necessarily actionable and some get stuck in queues or big data batch processing.

Cost-Benefit 78

Cost-Benefit Experimentation Testing Digital Transformation 78

Jet Global

NOVEMBER 5, 2020

Ostensibly, the new product represents Microsoft’s transition to a newer, more cloud-friendly ERP for midsized enterprises. OLAP reporting has traditionally relied on a data warehouse. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

datapine

AUGUST 29, 2022

The saying “knowledge is power” has never been more relevant, thanks to the widespread commercial use of big data and data analytics. The rate at which data is generated has increased exponentially in recent years. Essential Big Data And Data Analytics Insights. trillion each year.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

Jen Stirrup

MAY 5, 2020

It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. In this topic, we’re going to focus specifically on Big Data technologies, such as your HDInsight, Apache Spark and Databricks.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Analytics and intelligence for business users and user adoption.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

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

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. This is also true that decentralized data management is not new.

Management 66

Management Data Lake Uncertainty Data Warehouse 66

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. Reference data management.

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. This can be done with the help of socializing ideas within an Enterprise Business Intelligence tool, be it with or without an Enterprise Social Network (ESN). Summing Up.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

AWS Big Data

JANUARY 8, 2024

This is the first post to a blog series that offers common architectural patterns in building real-time data streaming infrastructures using Kinesis Data Streams for a wide range of use cases. In this post, we will review the common architectural patterns of two use cases: Time Series Data Analysis and Event Driven Microservices.

Analytics 109

Analytics IoT Data-driven Snapshot 109

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. Today, big data is about business disruption.

IT 317

IT Statistics KPI Data-driven 317

AWS Big Data

APRIL 25, 2024

This approach promotes efficiency, flexibility, and scalability, enabling large enterprises to meet their evolving needs and achieve their goals. As the queries finish running, an UNLOAD operation is invoked from the Redshift data warehouse to the S3 bucket in Account A. He has a keen interest in data analytics as well.

Metadata 94

Metadata Data Processing Management Testing 94

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. He is passionate about big data and data analytics. He helps enterprise customers migrate and modernize their data lake and data warehouse using AWS services.

Metadata 76

Metadata Testing Data Lake Consulting 76

FineReport

NOVEMBER 17, 2021

However, Tableau may not work for each enterprise in the world. Power BI, an open-source alternative to tableau, creates amazing data experiences, with memorable reports personalized with your KPI s and brand. By utilizing big data investments by connecting to all your data sources, Power BI upgrades insights across your organization.

KPI 52

KPI Dashboards Metadata Data Warehouse 52