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

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 89

Data Warehouse Optimization Analytics Sales 89

CIO Business Intelligence

DECEMBER 20, 2024

Beyond breaking down silos, modern data architectures need to provide interfaces that make it easy for users to consume data using tools fit for their jobs. Data must be able to freely move to and from data warehouses, data lakes, and data marts, and interfaces must make it easy for users to consume that data.

Data Architecture 122

Data Architecture Management Consulting Internet of Things 122

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 Visualization 270

AWS Big Data

FEBRUARY 26, 2025

Analytics remained one of the key focus areas this year, with significant updates and innovations aimed at helping businesses harness their data more efficiently and accelerate insights. This premier event showcased groundbreaking advancements, keynotes from AWS leadership, hands-on technical sessions, and exciting product launches.

Analytics 61

Analytics Data Lake Metadata Data Warehouse 61

AWS Big Data

NOVEMBER 22, 2024

Organizations run millions of Apache Spark applications each month on AWS, moving, processing, and preparing data for analytics and machine learning. Data practitioners need to upgrade to the latest Spark releases to benefit from performance improvements, new features, bug fixes, and security enhancements. This Glue 2.0

Cost-Benefit 105

Cost-Benefit Data-driven Software Testing 105

AWS Big Data

NOVEMBER 13, 2023

Join the AWS Analytics team at AWS re:Invent this year, where new ideas and exciting innovations come together. For those in the data world, this post provides a curated guide for all analytics sessions that you can use to quickly schedule and build your itinerary. Book your spot early for the sessions you do not want to miss.

Analytics 119

Analytics Data Lake Data Warehouse Data-driven 119

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 130

Analytics Machine Learning Data mining Data Quality 130

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

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

AWS Big Data

MAY 2, 2024

Amazon Redshift recently announced integration with Visual Studio Code (), an action that transforms the way data practitioners engage with Amazon Redshift and reshapes your interactions and practices in data management. Set up a Amazon Redshift or Amazon Redshift serverless data warehouse. Virginia)).

Visualization 119

Visualization Data Warehouse Data-driven Management 119

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 123

Analytics Finance B2B Reporting 123

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 134

Analytics IoT Data-driven Snapshot 134

AWS Big Data

MAY 28, 2024

Welcome back to our exciting exploration of architectural patterns for real-time analytics with Amazon Kinesis Data Streams! Before we dive in, we recommend reviewing Architectural patterns for real-time analytics using Amazon Kinesis Data Streams, part 1 for the basic functionalities of Kinesis Data Streams.

IoT 115

IoT Analytics Dashboards Data-driven 115

Occam's Razor

NOVEMBER 5, 2007

You are not going to solve my problem of getting a single source of truth for all my web data?" Not " singlecity ", not on the web, not in Web Analytics 2.0." But there were two concepts, one big and one small, that were key in developing my own thinking about web analytics. " Me : "Multiplicity.

Analytics 98

Analytics Experimentation Metrics Measurement 98

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

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

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 144

Data mining Data-driven Statistics OLAP 144

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

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. In fact, many commonly accepted best practices for designing OLTP databases could well be considered worst practices for these purely analytical systems. Analytical. Business Focus.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 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 134

Data Warehouse Dashboards Risk Management Risk 134

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

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

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 152

Testing Dashboards Measurement Experimentation 152

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 42

Data Warehouse Marketing Big Data Data-driven 42

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 144

Data mining Data Science Informatics Statistics 144

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 Measurement 91

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 131

Management Data Architecture Data Lake Data Strategy 131

AWS Big Data

MAY 28, 2024

The details of each step are as follows: Populate the Amazon Redshift Serverless data warehouse with company stock information stored in Amazon Simple Storage Service (Amazon S3). Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 118

Unstructured Data Data Warehouse Structured Data Testing 118

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 144

Cost-Benefit Digital Transformation Data Warehouse Data-driven 144

AWS Big Data

NOVEMBER 15, 2023

The analytics team is waiting to engage with our customers and partners at the analytics kiosk in the expo hall. For the latest and greatest with Amazon Redshift , our cloud data warehousing solution, I’ve curated a few must-attend sessions. But there are so many good ones on the list.

Data Lake 72

Data Lake Data Warehouse B2B Deep Learning 72

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 Data Warehouse Cost-Benefit Digital Transformation 98

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

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 Data-driven 111

Occam's Razor

APRIL 2, 2012

Two helpful blog posts on multi-channel analytics: 1. Such companies usually also own massive data warehouses where they have an ability to periodically do cannonballs into the data and identify correlations in consumption and purchase patterns. Tracking online impact of offline advertising. It's mandatory.

Modeling 154

Modeling Advertising Marketing Measurement 154

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 50

Publishing Analytics Business Intelligence Operational Reporting 50

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 121

Data Lake Unstructured Data Management Snapshot 121