AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

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

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

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

datapine

MARCH 31, 2022

On the flip side, if you enjoy diving deep into the technical side of things, with the right mix of skills for business intelligence you can work a host of incredibly interesting problems that will keep you in flow for hours on end. This could involve anything from learning SQL to buying some textbooks on data warehouses.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? One challenge in applying data science is to identify pertinent business issues.

Machine Learning 59

Machine Learning Data Science Statistics Deep Learning 59

IBM Big Data Hub

AUGUST 28, 2023

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. Users have become increasingly hungry for quicker access to trusted and timely data, and a way to access that data with less reliance on the busy Central Analytics Technology team.

Publishing 54

Publishing Analytics Business Intelligence Operational Reporting 54

datapine

SEPTEMBER 29, 2022

Today most of a company’s operations and strategic decisions heavily rely on data, so the importance of quality is even higher. And indeed, low-quality data is the leading cause of failure for advanced data and technology initiatives, to the tune of $9.7 1 – The people.

Data Quality 241

Data Quality Metrics Data-driven Management 241

erwin

APRIL 2, 2021

And knowing the business purpose translates into actively governing personal data against potential privacy and security violations. Do You Know Where Your Sensitive Data Is? Data is a valuable asset used to operate, manage and grow a business. Minimizing Risk Exposure with Data Intelligence.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Cloudera

SEPTEMBER 12, 2018

Last night we kicked it off with the sixth annual Data Impact Awards Celebration. These awards recognize organizations that transform complex data into actionable insights and illustrate impact to technology, science, health, lifestyle, and community across a wide variety of industries. Technical Impact. Special Impact.

Machine Learning 44

Machine Learning Big Data Data Science Data Warehouse 44

Sisense

OCTOBER 6, 2020

Despite its many uses, quantitative data presents two main challenges for a data-driven organization. First, data isn’t created in a uniform, consistent format. It’s generated by a host of sources in different ways. Advanced technology and new approaches are needed.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Most of the data management moved to back-end servers, e.g., databases.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

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

AWS Big Data

JANUARY 24, 2023

In this post, you will learn how to build a serverless analytics application using Amazon Redshift Data API and Amazon API Gateway WebSocket and REST APIs. The Data API simplifies access to Amazon Redshift because you don’t need to configure drivers and manage database connections.

Analytics 57

Analytics Data-driven Management Reporting 57

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

Testing 307

Testing Machine Learning Consulting Data Quality 307

Alation

JANUARY 17, 2023

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 ingestion/integration services. Data orchestration tools. In the past, data movement was defined by ETL: extract, transform, and load.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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 Intelligence 139

Business Intelligence Dashboards Data mining OLAP 139

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

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

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

IBM Big Data Hub

JULY 11, 2023

Data warehouses are a critical component of any organization’s technology ecosystem. The next generation of IBM Db2 Warehouse brings a host of new capabilities that add cloud object storage support with advanced caching to deliver 4x faster query performance than previously, while cutting storage costs by 34x 1.

Data Warehouse 51

Data Warehouse Testing Sales Dashboards 51

AWS Big Data

MAY 30, 2023

A host with the installed MySQL utility, such as an Amazon Elastic Compute Cloud (Amazon EC2) instance, AWS Cloud9 , your laptop, and so on. The host is used to access an Amazon Aurora MySQL-Compatible Edition cluster that you create and to run a Python script that sends sample records to the Kinesis data stream.

Data Lake 77

Data Lake Data Analytics Analytics Data Processing 77

Cloudera

AUGUST 21, 2020

And next to those legacy ERP, HCM, SCM and CRM systems, that mysterious elephant in the room – that “Big Data” platform running in the data center that is driving much of the company’s analytics and BI – looks like a great potential candidate. . What technologies will change or be available 3 years from now? .

Cost-Benefit 73

Cost-Benefit Big Data ROI Risk 73

IBM Big Data Hub

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

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. Technology underpinnings of blazingly fast databases.

Data-driven 75

Data-driven Data Warehouse Data Processing Marketing 75

AWS Big Data

FEBRUARY 21, 2023

Toucan natively integrates with Redshift Serverless, which enables you to deploy a scalable data stack in minutes without the need to manage any infrastructure component. Amazon Redshift is a fully managed cloud data warehouse service that enables you to analyze large amounts of structured and semi-structured data.

Visualization 52

Visualization Dashboards Data Warehouse Cost-Benefit 52

Cloudera

JANUARY 3, 2019

This year, we’re making a big one. On January 3, we closed the merger of Cloudera and Hortonworks — the two leading companies in the big data space — creating a single new company that is the leader in our category. They share a tremendous amount of common open source technology. We intend to win.

IoT 74

IoT Machine Learning Data Warehouse Enterprise 74

Cloudera

NOVEMBER 13, 2017

As the market moves toward cloud-based big data and analytics, three qualities emerge as vital for success. The net result is much improved productivity for data engineers, data scientists, and analysts. Unified – Conceptually, cloud sounds like a single place to host diverse, data-intensive functions.

Analytics 40

Analytics Big Data Machine Learning Cost-Benefit 40

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

AWS Big Data

NOVEMBER 8, 2023

Putting your data to work with generative AI – Innovation Talk Thursday, November 30 | 12:30 – 1:30 PM PST | The Venetian Join Mai-Lan Tomsen Bukovec, Vice President, Technology at AWS to learn how you can turn your data lake into a business advantage with generative AI. Reserve your seat now! Reserve your seat now!

Data-driven 87

Data-driven Data Lake Machine Learning Cost-Benefit 87

IBM Big Data Hub

JUNE 15, 2023

It is comprised of commodity cloud object storage, open data and open table formats, and high-performance open-source query engines. To help organizations scale AI workloads, we recently announced IBM watsonx.data , a data store built on an open data lakehouse architecture and part of the watsonx AI and data platform.

Data Warehouse 96

Data Warehouse Data Lake Optimization Data-driven 96

AWS Big Data

APRIL 25, 2023

Data and its various uses is increasingly evident in companies, and each professional has their preferences about which technologies to use to visualize data, which isn’t necessarily in line with the technological needs and infrastructure of a company.

Visualization 52

Visualization IT Data-driven Reporting 52

AWS Big Data

FEBRUARY 27, 2024

Each data producer within the organization has its own data lake in Apache Hudi format, ensuring data sovereignty and autonomy. This enables data-driven decision-making across the organization. AWS Glue – Bluestone used the AWS Glue PySpark environment for implementing data extract, transform, and load (ETL) processes.

Data-driven 93

Data-driven Data Lake Data Quality Data Governance 93

Cloudera

FEBRUARY 22, 2021

The Cloudera Data Platform (CDP) represents a paradigm shift in modern data architecture by addressing all existing and future analytical needs. In this introductory article, I present an overarching framework that captures the benefits of CDP for technology and business stakeholders. Technology cost reduction / avoidance.

Cost-Benefit 78

Cost-Benefit Data Warehouse Data Processing Data Governance 78

Cloudera

NOVEMBER 22, 2021

In legacy analytical systems such as enterprise data warehouses, the scalability challenges of a system were primarily associated with computational scalability, i.e., the ability of a data platform to handle larger volumes of data in an agile and cost-efficient way. Introduction. CRM platforms).

Data Processing 89

Data Processing Data Warehouse Enterprise Visualization 89

Cloudera

MAY 18, 2021

The intent of this article is to articulate and quantify the value proposition of CDP Public Cloud versus legacy IaaS deployments and illustrate why Cloudera technology is the ideal cloud platform to migrate big data workloads off of IaaS deployments. Technology and infrastructure costs . Deployment Type. Cost (in USD).

Cost-Benefit 84

Cost-Benefit Data-driven Data Warehouse Machine Learning 84

Cloudera

MARCH 22, 2022

Within that context, technology modernization will become a key prerequisite for unlocking value in M&A settings. This first article covers the benefits of Cloudera Data Platform for the integrating entities in Mergers and Acquisitions scenarios and the second article addresses Asset Divestitures / Carve-outs. .

Strategy 79

Strategy Cost-Benefit Risk Data Processing 79