datapine

SEPTEMBER 27, 2022

Business leaders, developers, data heads, and tech enthusiasts – it’s time to make some room on your business intelligence bookshelf because once again, datapine has new books for you to add. We have already given you our top data visualization books , top business intelligence books , and best data analytics books.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

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 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

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

CIO Business Intelligence

JANUARY 16, 2023

Kirkland, a founding member of SustainabilityIT.org, an organization to drive global sustainability through technology leadership, says Choice was the first hospitality company to make a strategic commitment to developing a cloud-native and sustainable platform on AWS. All the logic is still in Java hosted on Amazon’s infrastructure.”

Cost-Benefit 137

Cost-Benefit Digital Transformation Data Warehouse Data-driven 137

Cloudera

JANUARY 26, 2022

Modern, real-time businesses require accelerated cycles of innovation that are expensive and difficult to maintain with legacy data platforms. Cloud technologies and respective service providers have evolved solutions to address these challenges. . The amount of data being collected grew, and the first data warehouses were developed.

Data Processing 83

Data Processing IoT Cost-Benefit Digital Transformation 83

AWS Big Data

MAY 10, 2023

A write-back is the ability to update a data mart, data warehouse, or any other database backend from within BI dashboards and analyze the updated data in near-real time within the dashboard itself. AnyCompany currently uses Amazon Redshift as their enterprise data warehouse platform and QuickSight as their BI solution.

Dashboards 73

Dashboards Data Warehouse Visualization Data Processing 73

AWS Big Data

MARCH 10, 2023

They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. These transactional data lakes combine features from both the data lake and the data warehouse. Data can be organized into three different zones, as shown in the following figure.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

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

Smart Data Collective

NOVEMBER 18, 2020

You may not even know exactly which path you should pursue, since some seemingly similar fields in the data technology sector have surprising differences. We decided to cover some of the most important differences between Data Mining vs Data Science in order to finally understand which is which. Where to Use Data Mining?

Data mining 143

Data mining Data Science Informatics Statistics 143

Cloudera

MAY 2, 2018

Global Technology Partner of the Year. Qonnections is the premier Business Intelligence (BI) conference that brings data lovers together to share insights and discover data in new ways. The post Disrupting Everything in BI Analytics appeared first on Cloudera Blog.

Analytics 44

Analytics Business Intelligence Data Science Data Processing 44

AWS Big Data

JANUARY 24, 2023

Serverless applications are a modernized way to perform analytics among business departments and engineering teams. Reporting and analysis – An application where you can trigger large analytical queries with dynamic inputs and then view or download the results. What are WebSockets and why do we need them?

Analytics 57

Analytics Data-driven Management Reporting 57

Sisense

OCTOBER 10, 2019

Today I’m going to talk about how the cloud changed everything and what else this technology will bring to the table. It can’t be overstated: the rise of cloud storage and computing changed everything for companies and data engineers alike, and it’s never going back. Cloud changed everything. You’ll never own a server machine again.

Data Processing 60

Data Processing Data Warehouse Digital Transformation Software 60

Alation

JULY 13, 2021

This recent cloud migration applies to all who use data. We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. runs Advanced Analytics at TDWI.

Strategy 52

Strategy Data mining Structured Data Data Governance 52

Cloudera

MAY 12, 2021

2020 saw us hosting our first ever fully digital Data Impact Awards ceremony, and it certainly was one of the highlights of our year. We saw a record number of entries and incredible examples of how customers were using Cloudera’s platform and services to unlock the power of data. DATA FOR GOOD. INDUSTRY TRANSFORMATION.

Digital Transformation 66

Digital Transformation Machine Learning Optimization Data Lake 66

AWS Big Data

JULY 20, 2023

Apache Hive is a SQL-based data warehouse system for processing highly distributed datasets on the Apache Hadoop platform. The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table.

Data Lake 77

Data Lake Metadata Data Processing Big Data 77

erwin

APRIL 2, 2021

That’s especially true as the data-driven enterprise momentum grows along with self-service analytics that enable users to have greater access to information, often using it without IT’s knowledge. And knowing the business purpose translates into actively governing personal data against potential privacy and security violations.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

datapine

SEPTEMBER 29, 2022

6) Data Quality Metrics Examples. 7) Data Quality Control: Use Case. 8) The Consequences Of Bad Data Quality. 9) 3 Sources Of Low-Quality Data. 10) Data Quality Solutions: Key Attributes. And indeed, low-quality data is the leading cause of failure for advanced data and technology initiatives, to the tune of $9.7

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

JULY 23, 2019

With multiple sessions on VBA, macros, Jet products, data visualization, Power BI, PivotTables, dashboards, and the latest technology in Microsoft Excel – Excelapalooza is your reporting and analytics dreamland. Power BI Desktop opens a new era in data analysis and reporting. When: September 16th – 18th, 2019.

Dashboards 71

Dashboards Reporting Data Warehouse Visualization 71

Sisense

OCTOBER 6, 2020

The challenge comes when the data becomes huge and fast-changing. Why is quantitative data important? Quantitative data is often viewed as the bedrock of your business intelligence and analytics program because it can reveal valuable insights for your organization. It’s generated by a host of sources in different ways.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

IBM Big Data Hub

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. appeared first on IBM Blog.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

Cloudera

SEPTEMBER 12, 2018

The week is typically filled with exciting announcements from Cloudera and many partners and others in the data management, machine learning and analytics industry. Last night we kicked it off with the sixth annual Data Impact Awards Celebration. Modern Data Warehousing: Barclays (nominated together with BlueData ).

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

AWS Big Data

JULY 27, 2023

Amazon Redshift is a widely used, fully managed, petabyte-scale cloud data warehouse. Tens of thousands of customers use Amazon Redshift to process exabytes of data every day to power their analytics workloads. Amazon Redshift RA3 with managed storage is the newest instance type for Provisioned clusters.

Testing 64

Testing Data Warehouse Data Processing Snapshot 64

Howard Dresner

JANUARY 4, 2015

A lack of understanding about technology can breed distrust. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. So let’s look at why a BI initiative sometimes doesn’t fully deliver on its promise. Failures, after all, are very instructive. And good communications between all involved can reduce misunderstanding up front.

Business Intelligence 45

Business Intelligence Recreation/Entertainment Sales Data Quality 45

Cloudera

AUGUST 31, 2020

With data at the heart of its business, SMG has for many years pursued the most cutting-edge data management technologies. As SMG continued to innovate, the scale, variety and velocity of data made its legacy warehouse environment show its limits. The case for a new Data Warehouse?

Slice and Dice 63

Slice and Dice Management Data Warehouse Analytics 63

DataKitchen

APRIL 13, 2021

Testing and Data Observability. Process Analytics. We have also included vendors for the specific use cases of ModelOps, MLOps, DataGovOps and DataSecOps which apply DataOps principles to machine learning, AI, data governance, and data security operations. . Reflow — A system for incremental data processing in the cloud.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Sisense

FEBRUARY 17, 2021

With more people becoming digital citizens, the ability for an application to explode in popularity has all but rendered obsolete the traditional IT hosting mindset of discrete servers performing discrete tasks. Let’s dig into three hosting models that help organizations achieve cloud flexibility.

Data Processing 52

Data Processing Modeling Technology IT 52

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. A typical modern data stack consists of the following: A data warehouse.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

MAY 30, 2023

Customers have been using data warehousing solutions to perform their traditional analytics tasks. A host with the installed MySQL utility, such as an Amazon Elastic Compute Cloud (Amazon EC2) instance, AWS Cloud9 , your laptop, and so on. Create a Python file called generate-data-for-kds.py : $ python3 generate-data-for-kds.py

Data Lake 77

Data Lake Data Analytics Analytics Data Processing 77

CIO Business Intelligence

JANUARY 20, 2023

Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions. Business analytics, on the other hand, is predictive (what’s going to happen in the future?)

Business Intelligence 138

Business Intelligence Dashboards Data mining OLAP 138

Domino Data Lab

APRIL 3, 2019

For definitions, let’s start with a standard textbook/encyclopedia definition: “Data governance encompasses the people, processes, and information technology required to create a consistent and proper handling of an organization’s data across the business enterprise. ”. Some of the finer points seem amorphous at best.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Cloudera

OCTOBER 25, 2022

Enabling data and analytics in the cloud allows you to have infinite scale and unlimited possibilities to gain faster insights and make better decisions with data. Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

BizAcuity

MAY 10, 2022

Cloud technology and innovation drives data-driven decision making culture in any organization. It is the epitome of modern technology right now with multi-dimensional innovations shaping every layer. Cloud technology has been around since the mid-2000s. Cloud technology is a fascinating subject.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

AWS Big Data

OCTOBER 18, 2023

Apache Hive is a distributed, fault-tolerant data warehouse system that enables analytics at a massive scale. Spark SQL is an Apache Spark module for structured data processing. host') export PASSWORD=$(aws secretsmanager get-secret-value --secret-id $secret_name --query SecretString --output text | jq -r '.password')

Big Data 79

Big Data Data Processing Interactive Testing 79

IBM Big Data Hub

JULY 11, 2023

Data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics that enable faster decision making and insights.

Data Warehouse 51

Data Warehouse Testing Sales Dashboards 51

IBM Big Data Hub

JULY 17, 2023

Visual modeling: Delivers easy-to-use workflows for data scientists to build data preparation and predictive machine learning pipelines that include text analytics, visualizations and a variety of modeling methods. It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud.

Machine Learning 67

Machine Learning Data Warehouse Modeling Cost-Benefit 67

IBM Big Data Hub

MARCH 25, 2022

Guest blogger: Chief Technology Officer and Co-Founder: Adam Prout. One of the key challenges in distributed scale-out databases included how to deploy many hosts built with high availability and elasticity while keeping the familiar SQL interface. We founded MemSQL (the original name of SingleStore) in 2011.

Data-driven 75

Data-driven Data Warehouse Data Processing Marketing 75

Cloudera

OCTOBER 17, 2023

Recently, Confluent hosted Current 2023 (formerly Kafka summit) in San Jose on Sept 26th and 27th. Architecture decisions have long-term effects and an important consideration when choosing a stream processing engine is whether the technology will stagnate or continue to evolve with contributions from the open source community.

Data-driven 75

Data-driven Enterprise IoT Data Warehouse 75