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 102

Data Warehouse Testing Data Lake Data-driven 102

Smarten

DECEMBER 3, 2023

Reviewing Requirements Work with your IT team to review your existing infrastructure, network, hardware, and data storage and the landscape of solutions and apps that will require integration with the augmented analytics platform. What do you want to achieve by implementing an augmented analytics solution? in the discussion.

Analytics 40

Analytics Data Warehouse Metrics Interactive 40

Alation

FEBRUARY 13, 2020

Gartner’s Gareth Herschel, VP analyst, pointed out that although “Hotel Weird” presents a compelling novelty, machines just aren’t great at every aspect of service. Zaidi’s vision for the value of machine learning data catalogs closely resembles the data cataloging vision presented by our Cofounder Aaron Kalb at Strata + Hadoop World 2016.

Machine Learning 52

Machine Learning Data Analytics Analytics Metadata 52

AWS Big Data

NOVEMBER 9, 2023

It allows users to write data transformation code, run it, and test the output, all within the framework it provides. Use case The Enterprise Data Analytics group of a large jewelry retailer embarked on their cloud journey with AWS in 2021. Create boto3 client for Glue glue_client = boto3.client('glue',

Data Warehouse 113

Data Warehouse Testing Data Quality Reporting 113

CIO Business Intelligence

JUNE 23, 2023

There are also no-code data engineering and AI/ML platforms so regular business users, as well as data engineers, scientists and DevOps staff, can rapidly develop, deploy, and derive business value.

Data Strategy 116

Data Strategy Strategy Visualization Consulting 116

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Reference data management.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Cloudera

JANUARY 19, 2024

The generated SQL is presented in a modal together with the assumptions made by the LLM. Log in to the Cloudera Data Warehouse service as DWAdmin. Go to the virtual warehouse tab, locate the Virtual Warehouse on which you want to enable this feature, and click “edit.” Click “enter” to generate the SQL query.

Data Warehouse 71

Data Warehouse Data Processing Optimization Modeling 71

Sisense

APRIL 26, 2020

Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both. Structured vs unstructured data. However, both types of data play an important role in data analysis.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

datapine

JANUARY 24, 2021

This genie (who we’ll call Data Dan) embodies the idea of a perfect data analytics platform through his magic powers. Now, with Data Dan, you only get to ask him three questions. The questions to ask when analyzing data will be the framework, the lens, that allows you to focus on specific aspects of your business reality.

IT 317

IT Statistics KPI Data-driven 317

Laminar Security

DECEMBER 13, 2023

In fact, 68% of security professionals identify shadow data as their primary challenge. This is further exacerbated by the employment of outdated processes or solutions that are ill-equipped to cater to the demands of present-day cloud data security. Another critical challenge is bias and discrimination.

Data-driven 119

Data-driven Machine Learning Risk Deep Learning 119

DataKitchen

JANUARY 3, 2022

A DataOps process hub offers a way for business analytics teams to cope with fast-paced requirements without expanding staff or sacrificing quality. Analytics Hub and Spoke. The data analytics function in large enterprises is generally distributed across departments and roles. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

DataKitchen

OCTOBER 5, 2021

Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires.

Testing 152

Testing Dashboards Measurement Experimentation 152

BizAcuity

MAY 16, 2022

The more effectively a company uses data, the better it performs. Cutting down latency or delay is now one of the most crucial elements of business intelligence strategy in present times. Integrating data allows you to perform cross-database queries, which like portals provide you with endless possibilities. Data mining.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 79

Data Analytics Analytics IoT Data Lake 79

FineReport

NOVEMBER 17, 2021

FineReport: When organizing data management, we may face data source replacement. In SQL, the data source table name needs to be changed. An error message will then be presented if the field (syllable) is different. Automated insights and augmented analytics are also a good choice. Report and Dashboard.

KPI 52

KPI Dashboards Metadata Data Warehouse 52

AWS Big Data

APRIL 25, 2024

They also want to perform the data processing and transformation work in their own account (Account B) to compartmentalize duties and prevent any unintended changes to the source raw data present in the central account (Account A). data – Any datasets used in the DAG. He has a keen interest in data analytics as well.

Metadata 110

Metadata Data Processing Management Testing 110

AWS Big Data

APRIL 19, 2023

Many customers run big data workloads such as extract, transform, and load (ETL) on Apache Hive to create a data warehouse on Hadoop. sample_data/us_current.csv s3://$s3_bucket_name/covid-19-testing-data/base/source_us_current/; Copy states_current.csv : aws s3 cp./sample_data/states_current.csv

Metadata 83

Metadata Testing Data Lake Consulting 83

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.

Machine Learning 58

Machine Learning Data Science Statistics Deep Learning 58

datapine

MARCH 31, 2022

To simplify things, you can think of back-end BI skills as more technical in nature and related to building BI platforms, like online data visualization tools. Front-end analytical and business intelligence skills are geared more towards presenting and communicating data to others. Business Intelligence Job Roles.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Cloudera

MAY 15, 2019

He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange. The Enterprise Data Cloud – A Healthcare Perspective.

Enterprise 47

Enterprise Data Lake Data mining IoT 47

Smart Data Collective

JUNE 7, 2019

Using sensors, RFID tags and other tools can help deal with the flow of data in near real time. Volume – Companies gather data from different sources such as business transactions, social media, and other relevant data. It’s also a method of constant processing that takes place when big data is streaming into the system.

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

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

Jet Global

JANUARY 20, 2021

It’s hard to imagine taking that step, though, without first getting a handle on the organization’s existing data. Reining in all of this complexity is a critical first step in the process of creating a strategically relevant data analytics program. First, you must make all of those data available in a centralized repository.

Data Analytics 95

Data Analytics Management Analytics Data Warehouse 95

AWS Big Data

MAY 16, 2024

However, visualizing and analyzing large-scale geospatial data presents a formidable challenge due to the sheer volume and intricacy of information. With Amazon Redshift, you can get real-time insights and predictive analytics on all of your data across your operational databases, data lake, data warehouse, and third-party datasets.

Data Warehouse 107

Data Warehouse Visualization Cost-Benefit Optimization 107

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. What are WebSockets and why do we need them?

Analytics 60

Analytics Data-driven Management Reporting 60

AWS Big Data

OCTOBER 18, 2023

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse that provides the flexibility to use provisioned or serverless compute for your analytical workloads. Modern analytics is much wider than SQL-based data warehousing. Fault tolerance is built in. Any hardware failures are automatically replaced.

Analytics 102

Analytics Data Warehouse Testing Dashboards 102

AWS Big Data

JUNE 6, 2023

Unless, of course, the rest of their data also resides in the Google Cloud. 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 57

Analytics Data Lake Testing Optimization 57

AWS Big Data

OCTOBER 26, 2023

times better price-performance than other cloud data warehouses on real-world workloads using advanced techniques like concurrency scaling to support hundreds of concurrent users, enhanced string encoding for faster query performance, and Amazon Redshift Serverless performance enhancements. Amazon Redshift delivers up to 4.9

Data Warehouse 103

Data Warehouse Cost-Benefit Dashboards Optimization 103

BizAcuity

APRIL 14, 2022

Its effective data analytics that allows personalization in marketing & sales, identifying new opportunities, making important decisions and being sustainable for the long term. Competitive Advantages to using Big Data Analytics. With the amount of data being accumulated, it is easier when said.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. In many settings this is the best information available.

Data-driven 42

Data-driven Prescriptive Analytics Descriptive Analytics Machine Learning 42

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. What is a dimensional data model? What is a dimensional data model?

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

Cloudera

OCTOBER 29, 2020

Included with CDP Data Warehouse and Machine Learning, DV enables data engineers, data scientists, business analysts, and business users to create and share important insights instantly across any team using an intuitive drag-and-drop interface. Accelerate Collaboration Across The Lifecycle.

Visualization 106

Visualization Machine Learning Dashboards Data Warehouse 106

CIO Business Intelligence

MAY 24, 2022

Organisations have to contend with legacy data and increasing volumes of data spread across multiple silos. To meet these demands many IT teams find themselves being systems integrators, having to find ways to access and manipulate large volumes of data for multiple business functions and use cases. zettabytes of data.

Data-driven 98

Data-driven Data Lake Data Warehouse Cost-Benefit 98

FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. I purchased a data analytics system, but my company did not use it ?

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84