Sisense

JULY 7, 2020

Today’s organizations are more data-driven than ever. Over a third of respondents to our State of Analytics and BI survey reported that they are currently focused on growing their use of analytics across their businesses. In-Warehouse Data Prep supports both AWS Redshift and Snowflake data warehouses.

Slice and Dice 92

Slice and Dice Data Warehouse Analytics Dashboards 92

IBM Big Data Hub

AUGUST 28, 2023

If you’re a reader, chances are good you’ve read a book from Macmillan. It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. For more than 10 years, the publisher has used IBM Cognos Analytics to wrangle its internal and external operational reporting needs.

Publishing 52

Publishing Analytics Business Intelligence Operational Reporting 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.

Data Warehouse 119

Data Warehouse Dashboards Risk Management Risk 119

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

Laminar Security

JULY 19, 2023

To effectively protect sensitive data in the cloud, cyber security personnel must ensure comprehensive coverage across all their environments; wherever data travels, including cloud service providers (CSPs), data warehouses, and software-as-a-service (SaaS) applications.

Data Warehouse 91

Data Warehouse Data-driven Data Governance Risk 91

datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. The data warehouse. 1) The raw data.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Sisense

MARCH 6, 2019

Every year there’s high anticipation to see what key message Gartner will present in the yearly Data & Analytics Summits. The crowd who attends these events are made mostly of analytics leaders in Enterprises. Analytics leaders can only get buy-in if people understand the story of the journey and its purpose.

Data Analytics 75

Data Analytics Analytics Experimentation Data-driven 75

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 135

Data mining Data-driven Statistics OLAP 135

Juice Analytics

NOVEMBER 11, 2021

The symptoms we see are varied: lack of management support, lack of end-user adoption; poorly defined requirements; data warehouse projects that never seem to finish. And for each of these problems, the data industry has crafted different “solutions” or technologies to try to address them. We wrote a book about it.

Dashboards 137

Dashboards Data Warehouse Reporting Technology 137

CIO Business Intelligence

NOVEMBER 28, 2023

This means excelling in the under-the-radar disciplines of data architecture and data governance. Emotionally, culturally, and psychologically data management has to be rebranded — in the words of Sumathi Thiyagarajan , VP of business strategy and analytics for the Milwaukee Bucks — as “joyous” work.

Management 115

Management Data Architecture Data Lake Data Strategy 115

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines.

Testing 157

Testing Dashboards Measurement Experimentation 157

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. million searches per day and 1.2

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Cloudera

MARCH 2, 2022

Apache Impala is used today by over 1,000 customers to power their analytics in on premise as well as cloud-based deployments. Analytical SQL workloads use aggregates and joins heavily. Hence, optimizing such operators for both performance and efficiency in analytical engines like Impala can be very beneficial.

Data Warehouse 85

Data Warehouse Optimization Analytics Sales 85

CIO Business Intelligence

JANUARY 16, 2023

Aside from the core cloud services, Choice also uses Amazon RedShift as a front end to its cloud data warehouse, Amazon SageMaker to build machine leaning models, and Amazon Kinesis to collect, process, and analyze real-time data. All the logic is still in Java hosted on Amazon’s infrastructure.”

Cost-Benefit 142

Cost-Benefit Digital Transformation Data Warehouse Data-driven 142

AWS Big Data

MARCH 25, 2024

This dynamic integration of streaming data enables generative AI applications to respond promptly to changing conditions, improving their adaptability and overall performance in various tasks. To better understand this, imagine a chatbot that helps travelers book their travel.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

datapine

MARCH 31, 2022

Moreover, companies that use BI analytics are five times more likely to make swifter, more informed decisions. Despite these findings, the undeniable value of intelligence for business, and the incredible demand for BI skills, there is a severe shortage of BI-based data professionals – with a shortfall of 1.5

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

DECEMBER 16, 2022

You have a specific book in mind, but you have no idea where to find it. You enter the title of the book into the computer and the library’s digital inventory system tells you the exact section and aisle where the book is located. It uses metadata and data management tools to organize all data assets within your organization.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Alation

JULY 30, 2021

A part of that journey often involves moving fragmented on-premises data to a cloud data warehouse. You clearly shouldn’t move everything from your on-premises data warehouses. Otherwise, you can end up with a data swamp. But how do you do so effectively and efficiently? until 1 and 2 are addressed).

Data Warehouse 52

Data Warehouse Data Governance Machine Learning Data-driven 52

Smart Data Collective

NOVEMBER 18, 2020

Data Science is used in different areas of our life and can help companies to deal with the following situations: Using predictive analytics to prevent fraud Using machine learning to streamline marketing practices Using data analytics to create more effective actuarial processes. Where to Use Data Mining?

Data mining 143

Data mining Data Science Informatics Statistics 143

Cloudera

FEBRUARY 16, 2021

Cloudera Operational Database enables developers to quickly build future-proof applications that are architected to handle data evolution. Many business applications such as flight booking and mobile banking rely on a database that can scale and serve data at low latency. Cloudera Data Warehouse to perform ETL operations.

Machine Learning 81

Machine Learning Data Lake Enterprise Data Warehouse 81

Occam's Razor

JANUARY 24, 2011

The way OOD manifests itself is that in every website and web business I work with I am obnoxiously persistent in helping identify the desired outcomes of the site / business before I ever log into their web analytics data. Without goals and goal values you are not doing web analytics, you are doing web iamwastingyourlifeandminelytics.

Analytics 122

Analytics Finance B2B ROI 122

Andrew White

DECEMBER 4, 2019

I argued that one vendors’ book on data quality was really about data governance; I argued that another vendors’ marketing message was totally upside down; and I argued that some approaches to achieving single source of truth were different from traditional approaches. That’s the way it is.

Digital Transformation 64

Digital Transformation Data Integration Data Quality Data Warehouse 64

IBM Big Data Hub

NOVEMBER 8, 2023

We are expanding IBM Db2 Warehouse on Power with a new Base Rack Express at a 30% lower entry list price, adding to today’s S, M and L configurations, while still providing the same total-solution experience, including Db2 Data Warehouse’s connectivity with watsonx.data to unlock the potential of data for analytics and AI.

Strategy 96

Strategy Cost-Benefit Digital Transformation Data-driven 96

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Each card or listing contains information about a book or publication (e.g.,

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Jet Global

DECEMBER 8, 2020

If your company is planning to implement Microsoft’s Power BI analytics platform , it is critically important that you understand the complexity involved with a complete implementation. For more information about the risks of Power BI, download our FREE e-book, 5 Unknown Facts about Power BI That Create Project Risk.

Finance 52

Finance Risk Reporting Software 52

DataKitchen

DECEMBER 7, 2021

Back by popular demand, we’ve updated our data nerd Gift Giving Guide to cap off 2021. We’ve kept some classics and added some new titles that are sure to put a smile on your data nerd’s face. Here are eight highly recommendable books to help you find that special gift. ?? ?? ???. How did we get here?

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 129

Analytics Machine Learning Software Data Quality 129

Alation

JUNE 14, 2023

She adds that whenever she talks about data mesh, “I focus on the people piece of it, because it’s people who are actually going to drive it forward.” It’s also the mechanism that brings data consumers and data producers closer together. Register (and book a meeting with our team). Interested to learn more?

Data-driven 52

Data-driven Finance Uncertainty Digital Transformation 52

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. First, we’ll dive into the two types of databases: OLAP (Online Analytical Processing) and OLTP (Online Transaction Processing). So let’s dive in!

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

Cloudera

DECEMBER 12, 2018

I was a student system administrator for the campus computing group and at that time they were migrating the campus phone book to a new tool, new to me, known as Oracle. After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer.

Data Warehouse 41

Data Warehouse Marketing Big Data Data Lake 41

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. Our BI Best Practices demystify the analytics world and empower you with actionable how-to guidance. When BI and analytics users want to see analytics results, and learn from them quickly, they rely on data visualizations.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

IBM Big Data Hub

APRIL 8, 2024

Answer : Along with standard RDS features, Amazon RDS for Db2 supports key Db2 features, such as row and column organized tables for mixed and analytic workloads, the Adaptive Workload Optimizer to for better resource management, and rules-based access controls for advanced data protection.

Snapshot 74

Snapshot Data Warehouse Data Processing Management 74

Occam's Razor

MARCH 10, 2015

In a Q&A after a keynote a couple of years ago, I was asked: " When will traditional business analysis subsume the web analytics silo? " " My reply: " All business will ultimately be digital, so, if anything, web analytics will subsume business analysis! " Universal Analytics: What the heck is it?

Strategy 151

Strategy Analytics Measurement Business Analysis 151

AWS Big Data

SEPTEMBER 13, 2023

The Analytics specialty practice of AWS Professional Services (AWS ProServe) helps customers across the globe with modern data architecture implementations on the AWS Cloud. The following diagram represents a generic data lake architecture. The data lake source and target systems have their respective DR environments.

Data Lake 87

Data Lake Data Processing Metadata Snapshot 87

CIO Business Intelligence

OCTOBER 18, 2022

So, each band can send out 500KB to 750KB of data. To handle the huge volume of data thus generated, the company is in the process of deploying a data lake, data warehouse, and real-time analytical tools in a hybrid model. Lost and found tracking will be improved based on the guest routes. “In

Data Lake 98

Data Lake Cost-Benefit Digital Transformation Data Warehouse 98

Jet Global

MAY 27, 2022

Synapse services are powerful tools for bringing data together for analytics, machine learning, reporting needs, and more. How Synapse works with Data Lakes and Warehouses. Synapse services, data lakes, and data warehouses are often discussed together. Book A Demo.

Data Lake 52

Data Lake IT Recreation/Entertainment Data Warehouse 52

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 105

Data Architecture Data Integration IoT Strategy 105