AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 99

Data Warehouse Testing Data Lake Data-driven 99

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

AWS Big Data

FEBRUARY 16, 2024

Many customers are extending their data warehouse capabilities to their data lake with Amazon Redshift. They are looking to further enhance their security posture where they can enforce access policies on their data lakes based on Amazon Simple Storage Service (Amazon S3).

Data Lake 100

Data Lake Data Warehouse Testing Business Objectives 100

IBM Big Data Hub

NOVEMBER 6, 2023

This method requires the enterprise to have clean data flows from central sources of truth to accurately track and reflect usage. Watsonx.data allows enterprises to centrally gather, categorize and filter data from multiple sources. Less than 15% of SMBs want to interact with providers through phone and automated voice systems.

Cost-Benefit 109

Cost-Benefit Enterprise ROI Data Warehouse 109

IBM Big Data Hub

OCTOBER 30, 2023

IBM and AWS partnership focuses on delivering solutions in areas like: Supply chain optimization with AI-infused Planning Analytics IBM Planning Analytics on AWS offers a powerful platform for supply chain optimization, blending IBM’s analytics expertise with AWS’s cloud capabilities.

Insurance 84

Insurance Data Warehouse Data-driven Unstructured Data 84

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Cloudera

JULY 14, 2023

Introduction For more than a decade now, the Hive table format has been a ubiquitous presence in the big data ecosystem, managing petabytes of data with remarkable efficiency and scale. Depending on the size and usage patterns of the data, several different strategies could be pursued to achieve a successful migration.

Snapshot 69

Snapshot Metadata Data Warehouse Testing 69

AWS Big Data

MAY 18, 2023

You can discover and connect to over 70 diverse data sources, manage your data in a centralized data catalog, and create, run, and monitor data integration pipelines to load data into your data lakes and your data warehouses. AWS Glue released version 4.0 runtime ( 3.5 Since AWS Glue 4.0,

Testing 78

Testing Data Lake Cost-Benefit Data Integration 78

Cloudera

FEBRUARY 7, 2019

The company sought a data management platform that would allow its enterprise to handle greater data variety, velocity and volume in a cost-effective manner. This has become a core component of the fraud management framework for the business, and has helped solidify its role as the trusted keeper of sensitive data.

Big Data 64

Big Data Data Analytics Analytics Data Architecture 64

Cloudera

JANUARY 20, 2021

Most of what is written though has to do with the enabling technology platforms (cloud or edge or point solutions like data warehouses) or use cases that are driving these benefits (predictive analytics applied to preventive maintenance, financial institution’s fraud detection, or predictive health monitoring as examples) not the underlying data.

Digital Transformation 105

Digital Transformation Manufacturing Data Warehouse Predictive Analytics 105

AWS Big Data

OCTOBER 20, 2023

Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is passionate about architecting fast-growing data environments, diving deep into distributed big data software like Apache Spark, building reusable software artifacts for data lakes, and sharing knowledge in AWS Big Data blog posts.

Data Lake 86

Data Lake Big Data Consulting Data Warehouse 86

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Complete the implementation tasks such as data ingestion and performance testing. Analyze the data and then optimize as necessary.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

Cloudera

DECEMBER 19, 2018

Natural language analytics and streaming data analytics are emerging technologies that will impact the market. Cloud computing has passed the tipping point, with most organizations comfortable moving critical data and applications to the public cloud. Big Data Technologies and Architectures.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

IBM Big Data Hub

APRIL 28, 2022

To truly understand the data fabric’s value, let’s look at a retail supply chain use case where a data scientist wants to predict product back orders so that they can maintain optimal inventory levels and prevent customer churn. Learn more about a data fabric architecture and how it can benefit your organization.

Metadata 84

Metadata Data Warehouse Forecasting Predictive Modeling 84

Sisense

APRIL 2, 2020

Tools of the Trade is your destination for data and analytics skill building: From dashboards and reports to embedding analytics and building custom analytic apps to SQL secrets and data deep-dives, whatever you need to know to be better at your job, you can find it here. How to Choose a Database to Solve Your Data Challenges.

Data Warehouse 83

Data Warehouse Big Data Testing Software 83

AWS Big Data

JUNE 23, 2023

This blog post is co-written with Ori Nakar from Imperva. Events and many other security data types are stored in Imperva’s Threat Research Multi-Region data lake. Imperva harnesses data to improve their business outcomes. SPICE provides consistently fast query performance and automatically scales for high concurrency.

Data Lake 69

Data Lake Cost-Benefit Dashboards Data Warehouse 69

Sisense

JUNE 8, 2020

Every company is becoming a data company. In Data-Powered Businesses , we dive into the ways that companies of all kinds are digitally transforming to make smarter data-driven decisions, monetize their data, and create companies that will thrive in our current era of Big Data.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

BizAcuity

MAY 16, 2022

When data is stored in silos and the back-end systems are not able to process the massive amounts of data seamlessly, critical information may be lost. We get critical business insights based on how well we leverage our business data. The more effectively a company uses data, the better it performs. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

JANUARY 17, 2024

The key idea behind incremental queries is to use metadata or change tracking mechanisms to identify the new or modified data since the last query. By identifying these changes, the query engine can optimize the query to process only the relevant data, significantly reducing the processing time and resource requirements.

Data Lake 96

Data Lake Snapshot Big Data Data-driven 96

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 58

Machine Learning Data Science Statistics Deep Learning 58

CDW Research Hub

APRIL 20, 2020

Many organizations move from a traditional data warehouse to a hybrid or cloud-based data warehouse to help alleviate their struggles with rapidly expanding data, new users and use cases, and a growing number of diverse tools and applications. Connecting ThoughtSpot and Snowflake is a simple 3-step process.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

Sisense

APRIL 26, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. Structured vs unstructured data.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Sisense

JANUARY 13, 2020

In Moving Parts , we explore the unique data and analytics challenges manufacturing companies face every day. The world of data in modern manufacturing. From a practical perspective, the computerization and automation of manufacturing hugely increase the data that companies acquire. How data enhances product development.

Manufacturing 52

Manufacturing Data Lake Big Data Data Warehouse 52

AWS Big Data

JANUARY 8, 2024

Therefore, it is critical for organizations to embrace a low-latency, scalable, and reliable data streaming infrastructure to deliver real-time business applications and better customer experiences. Using a data stream in the middle provides the advantage of using the time series data in other processes and solutions at the same time.

Analytics 115

Analytics IoT Data-driven Snapshot 115

IBM Big Data Hub

OCTOBER 16, 2023

How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence.

Risk 76

Risk Modeling Management Metadata 76

AWS Big Data

APRIL 20, 2023

Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse. Amazon Redshift integration for Apache Spark helps developers seamlessly build and run Apache Spark applications on Amazon Redshift data.

Data Lake 78

Data Lake Data Warehouse Sales Data-driven 78

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. DeeQu is optimized to run data quality rules in minimal passes that makes it efficient.

Data Quality 95

Data Quality Statistics Data Lake Visualization 95

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. A metric to evaluate timeliness is the data time-to-value.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

MARCH 2, 2023

We use iceberg-blog-cluster. spark.sql.catalog.demo.warehouse – The demo Spark catalog stores all Iceberg metadata and data files under the root path defined by this property: s3://iceberg-curated-blog-data. impl – Iceberg allows users to write data to Amazon S3 through S3FileIO. all_reviews ): data and metadata.

Data Lake 119

Data Lake Data Processing Metadata Snapshot 119

IBM Big Data Hub

OCTOBER 16, 2023

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

AWS Big Data

MAY 25, 2023

Many organizations today are using AWS Glue to build ETL pipelines that bring data from disparate sources and store the data in repositories like a data lake, database, or data warehouse for further consumption. jobs because this feature will help reduce cost and optimize your ETL jobs.

Reporting 70

Reporting Metrics Optimization Data Lake 70

AWS Big Data

JUNE 6, 2023

This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake.

Analytics 56

Analytics Data Lake Testing Optimization 56

IBM Big Data Hub

JULY 5, 2022

Nedbank builds a scalable data warehouse architecture . Endless data but your queries aren’t fast enough. Empower real-time decision making and perform heavy computational analysis with built-in ML, insanely fast ingest, and querying of data in motion and at rest. Exxon transforms customer experiences .

Data Lake 94

Data Lake Data Warehouse Publishing Structured Data 94

Cloudera

MAY 16, 2019

The traditional Data Warehouse ETL process has splintered into many smaller components. Ingest is now focused data capture and real-time trend analysis where possible. Once data is brought under control in a system like Cloudera, then the work of Data Preparation, Quality begins. ENABLING CUSTOMER SUCCESS.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. Today, big data is about business disruption.

IT 317

IT Statistics KPI Data-driven 317