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.

Analytics 92

Analytics IT Data Lake Visualization 92

CIO Business Intelligence

OCTOBER 26, 2023

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 127

Business Intelligence Data-driven Statistics Data Warehouse 127

AWS Big Data

APRIL 3, 2024

Manage your Iceberg table with AWS Glue You can use AWS Glue to ingest, catalog, transform, and manage the data on Amazon Simple Storage Service (Amazon S3). With AWS Glue, you can discover and connect to more than 70 diverse data sources and manage your data in a centralized data catalog. Nidhi Gupta is a Sr.

Data Lake 91

Data Lake Snapshot Metadata Data Architecture 91

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 106

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 106

Smart Data Collective

APRIL 15, 2021

Business Intelligence is the practice of collecting and analyzing data and transforming it into useful, actionable information. In order to make good business decisions, leaders need accurate insights into both the market and day-to-day operations. Set Up Data Integration.

Business Intelligence 97

Business Intelligence Analytics Statistics Data Warehouse 97

Alation

JULY 28, 2022

But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. And adoption is so significant that many participants have earned notable market capitalization. And what must organizations overcome to succeed at cloud data warehousing ? Many see the cloud as the most secure option.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

FineReport

AUGUST 14, 2020

For popular reporting tools on the market, you can refer to: Best Reporting Tools List in 2020 and How to Choose. Based on the process from data to knowledge, a standard reporting system’s functional architecture is shown below. It is composed of three functional parts: the underlying data, data analysis, and data presentation.

Reporting 98

Reporting Informatics OLAP Data Warehouse 98

Andrew White

DECEMBER 4, 2019

Otherwise I don’t feel a need to repeat vendor marketing messages or product announcements since such vendors are quite capable, and motivated, to do that themselves. This acquisition followed another with Mulesoft, a data integration vendor. The marketing messages were all in point and being presented just as the vendor wanted.

Digital Transformation 64

Digital Transformation Data Integration Data Quality Data Warehouse 64

BizAcuity

MAY 16, 2022

Data allowed Guinness to hold their market dominance for long. Now, businesses, regardless of the industry, are leveraging data and Business Intelligence to stay ahead of the competition. We get critical business insights based on how well we leverage our business data. So, make sure you have a data strategy in place.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Data Virtualization

MARCH 31, 2022

Reading Time: 4 minutes A discussion on All Things Data with Katrina Briedis, Senior Product Marketing Manager (APAC) at Denodo, with a special focus on Data Fabric Approach for Effective Data Management. Listen to “Is Data Fabric the Ideal Approach for Effective Data Management?”

Management 52

Management Data Integration Marketing Data Lake 52

Cloudera

JUNE 2, 2022

One of the critical requirements that has materialized is the need for companies to take control of their data flows from origination through all points of consumption both on-premise and in the cloud in a simple, secure, universal, scalable, and cost-effective way. What are the key capabilities that a data distribution service has to have?

Enterprise 101

Enterprise Data Lake Data Collection Data-driven 101

Alation

APRIL 14, 2023

Last week, the Alation team had the privilege of joining IT professionals, business leaders, and data analysts and scientists for the Modern Data Stack Conference in San Francisco. In “The modern data stack is dead, long live the modern data stack!” Cloud costs are growing prohibitive.

Data Warehouse 52

Data Warehouse Data-driven Digital Transformation Metadata 52

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. Brian Ross is a Senior Software Development Manager at AWS.

Data Quality 92

Data Quality Statistics Data Lake Visualization 92

Data Virtualization

MAY 13, 2022

Reading Time: 3 minutes Join our conversation on All Things Data with Robin Tandon, Director of Product Marketing at Denodo (EMEA & LATAM), with a focus on how data virtualization helps customers realize true economic benefits in as little as six weeks.

Data Integration 52

Data Integration Marketing Management Data Warehouse 52

Cloudera

MAY 16, 2019

The conference provides a useful opportunity to reflect on the rapid evolution we’ve seen in the Data Integration and Management space, much of it driven by the innovations that Cloudera and the open source community have been delivering. The traditional Data Warehouse ETL process has splintered into many smaller components.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

Alation

DECEMBER 15, 2022

Like sports, vendors enjoy healthy competition and often find themselves in highly contested markets with several viable opponents, both big and small. These select athletes are determined by what the “market” is saying – this includes fans, analysts, and the press. How Do You Determine the GOAT for a Software Category?

Metadata 52

Metadata Data Governance Data Quality Marketing 52

CIO Business Intelligence

JULY 13, 2022

One of the critical requirements that has materialized is the need for companies to take control of their data flows from origination through all points of consumption both on-premise and in the cloud in a simple, secure, universal, scalable, and cost-effective way. What are the key capabilities that a data distribution service has to have?

Enterprise 77

Enterprise Data Lake Data Collection Data-driven 77

Sisense

JULY 2, 2020

Many popular cloud analysis tools, including Sisense for Cloud Data Teams, support both on-premise database servers and cloud data warehouses. When companies use cloud applications (for example, Salesforce) they need to get that data from the cloud and into their databases for analysis. Connections to Data Sources.

Data Warehouse 98

Data Warehouse Data Integration Software Marketing 98

Cloudera

FEBRUARY 11, 2019

The January 2019 “Magic Quadrant for Data Management Solutions for Analytics” provides valuable insights into the status, direction, and players in the DMSA market. In this blog, we share our takeaways as they relate to the DMSA market trends. 3. Expansion beyond core data management. Cloudera’s Positioning.

Management 43

Management Metadata Analytics Machine Learning 43

FineReport

MAY 31, 2023

Financial indicators, such as revenue, gross profit, asset to debt ratio, current ratio, turnover, and price-earnings (P/E) ratio, serve as key measures of profitability, solvency, operational capability, and market valuation. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

CIO Business Intelligence

JUNE 7, 2022

Because of this, only a small percentage of your AI team will work on data science efforts, he says. The rest of the team will identify the problem being solved, help explain the data, help organize the data, integrate the output into another production system, or present the data in a presentation-ready manner.”.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

Smarten

DECEMBER 7, 2017

In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to data warehouses and data marts and lots of complicated massaging and manipulation of data across other data sources.

IT 40

IT Testing ROI Data Warehouse 40

Andrew White

OCTOBER 22, 2021

Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. VP Data and Analytics 1. VP Data Science 1. Director Product Marketing 1.

IT 52

IT Data Lake Strategy Data Science 52

Ontotext

MARCH 8, 2023

Graphs boost knowledge discovery and efficient data-driven analytics to understand a company’s relationship with customers and personalize marketing, products, and services. Use Case #4: Financial Risk Detection and Prediction The financial industry is made up of a network of markets and transactions. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

FineReport

MAY 9, 2020

Therefore, shortens time to market and reduces the cost to integrate new features into software as a service (SaaS), Cloud, and on-premise applications. The data layer of FineReport is responsible for data management, including data collection, ETL, building a data warehouse, etc.

Reporting 52

Reporting Sales Data Warehouse Software 52

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88

BI-Survey

AUGUST 21, 2020

Especially in times of rapidly changing markets, decision-support systems should promote the quickest possible knowledge growth. Advanced analytics and new ways of working with data also create new requirements that surpass the traditional concepts. But what are the right measures to make the data warehouse and BI fit for the future?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

AWS Big Data

MARCH 27, 2024

AWS has invested in a zero-ETL (extract, transform, and load) future so that builders can focus more on creating value from data, instead of having to spend time preparing data for analysis. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 87

Data Analytics Analytics Data Warehouse Data Lake 87

Birst BI

OCTOBER 30, 2018

This may involve integrating different technologies, like cloud sources, on-premise databases, data warehouses and even spreadsheets. Add the predictive logic to the data model. With the source data now fully integrated into an analytic model, add and test different predictive algorithms.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

Data Warehouse 95

Data Warehouse Data Integration Marketing Software 95

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Reverse ETL tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

CIO Business Intelligence

APRIL 5, 2022

Investment in data warehouses is rapidly rising, projected to reach $51.18 billion by 2028 as the technology becomes a vital cog for enterprises seeking to be more data-driven by using advanced analytics. Data warehouses are, of course, no new concept. More data, more demanding. “As

Data Warehouse 98

Data Warehouse Visualization Data-driven Data Architecture 98

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

CIO Business Intelligence

NOVEMBER 29, 2022

Here, I’ll highlight the where and why of these important “data integration points” that are key determinants of success in an organization’s data and analytics strategy. For data warehouses, it can be a wide column analytical table. Data and cloud strategy must align.

Data Architecture 111

Data Architecture Data Integration IoT Strategy 111

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 112

Data Strategy Strategy Data Governance Marketing 112

CIO Business Intelligence

MAY 10, 2022

A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. Customer data platform benefits. By applying machine learning to the data, you can better predict customer behavior.

Advertising 121

Advertising Interactive Marketing Data Integration 121