FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They collaborate with cross-functional teams to meet organizational objectives and work across diverse sectors, including business intelligence, finance, marketing, and consulting.

Statistics 52

Statistics Data mining Visualization Reporting 52

Alation

JANUARY 26, 2023

Data is a key asset for businesses in the modern world. Used correctly, it can improve internal operations, power marketing strategies, and much more. That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

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

AWS Big Data

MARCH 1, 2024

It provides personal and commercial banking, global markets, and investment banking services to 13 million customers. As they continue to implement their Digital First strategy for speed, scale and the elimination of complexity, they are always seeking ways to innovate, modernize and also streamline data access control in the Cloud.

Data Lake 97

Data Lake Data Warehouse Management Risk 97

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

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 Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

IBM Big Data Hub

DECEMBER 7, 2023

Increased operational efficiency benefits Reduced data preparation time : OLAP data preparation capabilities streamline data analysis processes, saving time and resources. Real-time data insights : OLAP can provide real-time insights into business operations, enabling businesses to respond quickly to changing market conditions.

OLAP 64

OLAP Slice and Dice Cost-Benefit Data Warehouse 64

Alation

JULY 19, 2022

Finally, a data catalog can help data scientists find answers to their questions (and avoid re-asking questions that have already been answered). Modern data catalogs surface a wide range of data asset types. Modern data catalogs also facilitate data quality checks. Read the case study.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Alation

MARCH 21, 2023

What types of data are collected? With data analytics , travel organizations can gain real-time insights about customers to make strategic decisions and improve their travel experience. Data-driven marketing Using historical customer data, companies can market travel deals or pricing based on people’s known interests and needs.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

datapine

AUGUST 29, 2022

This process often comes with challenges related to scalability, consistency, reliability, efficiency, and maintainability, not to mention dealing with the number of software and technologies available in the market. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

MARCH 22, 2022

To compete in a digital economy, it’s essential to base decisions and actions on accurate data, both real-time and historical. Data about customers, supply chains, the economy, market trends, and competitors must be aggregated and cross-correlated from myriad sources. . Set up unified data governance rules and processes.

Analytics 115

Analytics Key Performance Indicator Data Warehouse Data-driven 115

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. With Netezza support for 1.2

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

Peter James Thomas

AUGUST 12, 2018

However, often the biggest stumbling block is a human one, getting people to buy in to the idea that the care and attention they pay to data capture will pay dividends later in the process. These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Metrics 49

Metrics Statistics Data Quality Measurement 49

AWS Big Data

MAY 1, 2024

To provide a variety of products, services, and solutions that are better suited to customers and society in each region, we have built business processes and systems that are optimized for each region and its market. Responsibilities include: Look for the data to be used from the technical data catalog and request access to the data.

Dashboards 102

Dashboards Data-driven Publishing Cost-Benefit 102

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 65

Data Architecture Data Lake Machine Learning Data Governance 65

CIO Business Intelligence

JANUARY 20, 2023

In particular, companies that were leaders at using data and analytics had three times higher improvement in revenues, were nearly three times more likely to report shorter times to market for new products and services, and were over twice as likely to report improvement in customer satisfaction, profits, and operational efficiency.

Data Lake 135

Data Lake Data-driven Finance Data Architecture 135

AWS Big Data

APRIL 5, 2023

Showpad aligns sales and marketing teams around impactful content and powerful training, helping sellers engage with buyers and generate the insights needed to continuously improve conversion rates. In 2021, Showpad set forth the vision to use the power of data to unlock innovations and drive business decisions across its organization.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Andrew White

MARCH 22, 2019

This ties into the failure of data governance and MDM (see first item in this list). A data hub strategy should be economical, not perfected; and a data hub does not collect data like a data warehouses or data lake does – they are very different things. Age maybe against us. All was going well.

Analytics 68

Analytics Metadata Data Governance Management 68

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52