CIO Business Intelligence

APRIL 8, 2025

We also examine how centralized, hybrid and decentralized data architectures support scalable, trustworthy ecosystems. As data-centric AI, automated metadata management and privacy-aware data sharing mature, the opportunity to embed data quality into the enterprises core has never been more significant.

Data Quality 102

Data Quality Data-driven Key Performance Indicator Metadata 102

CIO Business Intelligence

JANUARY 20, 2023

Improved employee satisfaction: Providing business users access to data without having to contact analysts or IT can reduce friction, increase productivity, and facilitate faster results. Increased competitive advantage: A sound BI strategy can help businesses monitor their changing market and anticipate customer needs.

Business Intelligence 144

Business Intelligence Dashboards Data mining OLAP 144

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

Jet Global

JANUARY 17, 2019

Otherwise, you’ll be building your analytics off bad data. Instead of an environment riddled with inaccuracies to base your analytics on, you need to be confident that your data is correct. This is where Master Data Management (MDM) comes into play. How MDM Can Prepare Your Data for BI. Download Now.

Business Intelligence 75

Business Intelligence Management Data Warehouse Data Governance 75

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. What does a business intelligence analyst do? The role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect through business intelligence strategies.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

datapine

FEBRUARY 22, 2022

Now we are going to take that a step further with the following 16 steps to a better business intelligence strategy. These steps are imperative for businesses, of all sizes, looking to successfully launch and manage their business intelligence. What Is A Business Intelligence Strategy? Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

Data Warehouse 97

Data Warehouse Dashboards Optimization Interactive 97

datapine

NOVEMBER 11, 2021

And not just that, with COVID-19 and remote work now being a permanent business practice, the need for more intuitive platforms that will facilitate teamwork has become critical. Business intelligence tools provide you with interactive BI dashboards that serve as powerful communication tools to keep teams engaged and connected.

Business Intelligence 213

Business Intelligence Dashboards Interactive Visualization 213

Cloudera

OCTOBER 4, 2023

A unique architecture to optimize for real-time data warehousing and business analytics: Cloudera Data Platform (CDP) offers Apache Kudu as part of our Data Hub cloud service, providing a consistent, dependable way to support the ingestion of data streams into our analytics environment, in real time, and at any scale.

Data Warehouse 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

Sisense

JUNE 26, 2019

The right tools and platforms that are easy to deploy, play well with legacy and modern systems, and can manage a complete end-to-end BI process, are what modern data engineers need in order to fully embrace complex data. As a data engineer, you need to build and manage data pipelines. The Right One.

Enterprise 75

Enterprise Data Warehouse Dashboards Modeling 75

Jet Global

JULY 11, 2019

By using a combination of data, statistical algorithms, and machine learning techniques, predictive analytics identifies the likelihood of future outcomes based on the past. While it’s not an exact science, demand forecasting plays a vital role in production planning and supply chain management. Data Consolidation.

Business Intelligence 72

Business Intelligence Forecasting Predictive Analytics Data Warehouse 72

Jet Global

FEBRUARY 5, 2019

But data has become increasingly complex, with high volumes from different sources spanning across multiple geographic regions. While we’ve seen a rise in technology investment that manages business processes and gathers data, it has greatly exceeded the time and resources put towards data management and governance.

Data Warehouse 69

Data Warehouse Data Quality Business Intelligence Data Governance 69

Cloudera

FEBRUARY 22, 2021

That benefit comes from Replication Manager , a key capability of CDP , that enables users to migrate existing, on-premises use cases to the public cloud with the same security and governance configurations. Those capabilities simplify Security Operations (“SecOps”) such as managing user authentication and authorization.

Cost-Benefit 82

Cost-Benefit Data Warehouse Data Processing Data Governance 82

Cloudera

DECEMBER 21, 2020

Company data exists in the data lake. Data Catalog profilers have been run on existing databases in the Data Lake. A Cloudera Data Warehouse virtual warehouse with Cloudera Data Visualisation enabled exists. A Cloudera Data Engineering service exists. The Data Scientist.

Dashboards 97

Dashboards Visualization Data Warehouse Data Lake 97

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 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 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

IBM Big Data Hub

OCTOBER 27, 2022

Lindt now has a team of 10, including a business intelligence (BI) manager and BI developer analysts. Yet Newcomp continues to be an essential and trusted partner, helping the company keep up with the high volume of analytics solutions it needs to address. Helping clients close the business analytics skills gap.

Slice and Dice 52

Slice and Dice Analytics Sales Business Analytics 52

Jet Global

MAY 1, 2020

The mechanical solution is to build a data warehouse. This will be the place where everybody has come together and agreed upon the data that you are going to use to manage your business, and how that data is going to be combined with which methods you’re going to use to calculate things like gross profit and net income.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

FineReport

NOVEMBER 25, 2020

Key performance indicators: Dashboard reporting tools bring together data from multiple areas displaying the information as easy to understand visuals in real-time. It provides managers with an overview of current KPIs to assess different performance areas while creating actionable insights. What Makes a Great Dashboard? From Google.

Dashboards 98

Dashboards Reporting Visualization Snapshot 98

Sisense

MAY 28, 2020

During our current pandemic, access to real-time data can also save lives. Health officials are investigating how contact-tracing apps can help manage the ‘reopening’ after we begin to reopen the country after the COVID-19 lockdown,” said George Thiruvathukal, professor of computer science at Loyola University in Chicago.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

IBM Big Data Hub

AUGUST 4, 2023

Data democratization is often conflated with data transparency, which refers to processes that help ensure data accuracy and easy access to data regardless of its location or the application that created it. This lets users across the organization treat the data like a product with widespread access.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. SECURITY AND GOVERNANCE LEADERSHIP. INDUSTRY TRANSFORMATION.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

Jet Global

OCTOBER 1, 2019

By using a combination of data, statistical algorithms, and machine learning techniques, predictive analytics identifies the likelihood of future outcomes based on the past. While it’s not an exact science, demand forecasting plays a vital role in production planning and supply chain management. Data Consolidation.

Business Intelligence 40

Business Intelligence Forecasting Predictive Analytics Data Warehouse 40

Jet Global

OCTOBER 22, 2020

The world of business analytics is evolving rapidly. The size and scope of business databases have grown as ERP functionality has evolved, businesses have increased their adoption of CRM and marketing automation, and collaboration networks have become more common. OLAP Cubes vs. Tabular Models. The first is an OLAP model.

Modeling 52

Modeling OLAP Reporting Sales 52

FineReport

APRIL 11, 2023

Additionally, they provide tabs, pull-down menus, and other navigation features to assist in accessing data. Data Visualizations : Dashboards are configured with a variety of data visualizations such as line and bar charts, bubble charts, heat maps, and scatter plots to show different performance metrics and statistics.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

Peter James Thomas

MAY 3, 2019

Control of Data to ensure it is Fit-for-Purpose. This refers to a wide range of activities from Data Governance to Data Management to Data Quality improvement and indeed related concepts such as Master Data Management. Data Architecture / Infrastructure. Best practice has evolved in this area.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

IBM Big Data Hub

AUGUST 28, 2023

For more than 10 years, the publisher has used IBM Cognos Analytics to wrangle its internal and external operational reporting needs. This encompasses their finance, sales, supply chain, inventory management and production areas.

Publishing 50

Publishing Analytics Business Intelligence Operational Reporting 50

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

Data Warehouse 105

Data Warehouse Snapshot Testing Management 105

CIO Business Intelligence

APRIL 9, 2025

For many, the level of sophistication can easily range from more sophisticated solutions like Power BI, Tableau, SAP Analytics or IBM Cognos to mid-tier solutions like Domo, Qlik or the tried and true elder statesman for all business analytics consumers, Excel.

Enterprise 102

Enterprise Analytics Experimentation Statistics 102

O'Reilly on Data

SEPTEMBER 11, 2019

The Strata Data Conferences helped chronicle the birth of big data, as well as the emergence of data science, streaming, and machine learning (ML) as disruptive phenomena. Strata attracts the leading names in the fields of data management, data engineering, analytics, ML, and artificial intelligence (AI).

IoT 25

IoT Big Data Data Warehouse Uncertainty 25

Occam's Razor

DECEMBER 3, 2008

2) You might have some project / task management experience, your leadership experience is limited to that. 3) I am simply assuming you are good at tools and some technical stuff and some business stuff. Do you like managing people? Project Manager. 2| Business Individual Contributor. And so on and so forth.

Analytics 115

Analytics Consulting Metrics Reporting 115

Occam's Razor

MARCH 10, 2015

For the rest of this post, I'll anchor the abilities of Universal Analytics to revolutionize your digital everything, by focusing on these three features. Dimension Widening – hello sweet simple data from spreadsheets, data warehouses/CRM systems! Measurement Protocol – all your data are belong to us!

Strategy 153

Strategy Analytics Measurement Business Analysis 153

Domino Data Lab

JULY 22, 2019

It involved a lot of interesting work on something new that was data management. I recently did “ Fifty Years of Data Management and Beyond ” which looks at roughly the same time period. Then in the bottom tier, you had your data management, your back office, right?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Peter James Thomas

AUGUST 18, 2018

From 2000 to 2015, I had some success [5] with designing and implementing Data Warehouse architectures much like the following: As a lot of my work then was in Insurance or related fields, the Analytical Repositories tended to be Actuarial Databases and / or Exposure Management Databases, developed in collaboration with such teams.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

datapine

AUGUST 29, 2022

Managing data in its full scope is not an easy task, especially when it comes to system design. Explaining the main concepts, going through the advantages and disadvantages of the tools and technologies available, and helping the reader navigate the complete landscape of data processing and storage.

Big Data 263

Big Data Data Analytics Analytics Data mining 263