Smart Data Collective

APRIL 2, 2019

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

Data Lake 83

Data Lake Big Data OLAP Testing 83

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 76

Data Analytics Analytics IoT Data Lake 76

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

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level. Choose Create.

Data Lake 83

Data Lake Data Governance Cost-Benefit Machine Learning 83

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 91

Metadata Data Lake Visualization Data Transformation 91

Sisense

MAY 28, 2019

2019 can best be described as an era of modern cloud data analytics. Convergence in an industry like data analytics can take many forms. We have seen industry rollups in which firms create a collection of analytical tools under one brand. The allure of operationalizing BI in-data is its perceived simplicity.

Data Analytics 89

Data Analytics Data Lake Analytics Unstructured Data 89

AWS Big Data

JUNE 6, 2023

It provides insights and metrics related to the performance and effectiveness of data quality processes. In this post, we highlight the seamless integration of Amazon Athena and Amazon QuickSight , which enables the visualization of operational metrics for AWS Glue Data Quality rule evaluation in an efficient and effective manner.

Data Quality 74

Data Quality Metrics Visualization Dashboards 74

AWS Big Data

MARCH 27, 2024

Amazon Redshift integrates with AWS HealthLake and data lakes through Redshift Spectrum and Amazon S3 auto-copy features, enabling you to query data directly from files on Amazon S3. This means you no longer have to create an external schema in Amazon Redshift to use the data lake tables cataloged in the Data Catalog.

Data Analytics 93

Data Analytics Analytics Data Warehouse Data Lake 93

AWS Big Data

JANUARY 12, 2024

We have defined all layers and components of our design in line with the AWS Well-Architected Framework Data Analytics Lens. Ingestion: Data lake batch, micro-batch, and streaming Many organizations land their source data into their data lake in various ways, including batch, micro-batch, and streaming jobs.

Data Lake 96

Data Lake Cost-Benefit Visualization Structured Data 96

Smart Data Collective

AUGUST 7, 2019

One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. The best thing that you can do is find some data analytics tools to solve your most pressing challenges. There are many benefits to data analytics.

Data Analytics 100

Data Analytics Analytics Big Data Data Lake 100

Jedox

OCTOBER 22, 2020

The term “data analytics” refers to the process of examining datasets to draw conclusions about the information they contain. Data analysis techniques enhance the ability to take raw data and uncover patterns to extract valuable insights from it. Data analytics is not new. Inability to get data quickly.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. Automation frees up both direct and indirect resources.

Consulting 244

Consulting Testing Data Lake Data Quality 244

DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

Testing 130

Testing Data Lake Dashboards Data Science 130

CIO Business Intelligence

JUNE 29, 2022

And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done. For many enterprises, Microsoft Azure has become a central hub for analytics. Azure Data Explorer. Azure Data Lake Analytics.

Data Lake 113

Data Lake Analytics Data Warehouse Machine Learning 113

AWS Big Data

NOVEMBER 6, 2023

Amazon EMR Studio is an integrated development environment (IDE) that makes it straightforward for data scientists and data engineers to develop, visualize, and debug data engineering and data science applications written in R, Python, Scala, and PySpark. This helps you reduce operational overhead.

Data Lake 96

Data Lake Sales Management Testing 96

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. AWS Glue provides both visual and code-based interfaces to make data integration effortless. Choose Create job and Visual ETL. Choose Create connection.

Analytics 98

Analytics IT Data Lake Visualization 98

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. This often overwhelms traditional visualization tools and methods. Figure 1 – Map built with CARTO Builder and the native support to visualize H3 indexes What are spatial indexes?

Data Warehouse 109

Data Warehouse Visualization Cost-Benefit Optimization 109

AWS Big Data

OCTOBER 23, 2023

Modern applications store massive amounts of data on Amazon Simple Storage Service (Amazon S3) data lakes, providing cost-effective and highly durable storage, and allowing you to run analytics and machine learning (ML) from your data lake to generate insights on your data.

Data Lake 104

Data Lake Visualization Optimization Interactive 104

AWS Big Data

MARCH 26, 2024

Strategize based on how your teams explore data, run analyses, wrangle data for downstream requirements, and visualize data at different levels. Plan on how you can enable your teams to use ML to move from descriptive to prescriptive analytics. QuickSight offers scalable, serverless visualization capabilities.

Data Strategy 70

Data Strategy Strategy Data Warehouse Prescriptive Analytics 70

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption. This is the Data Mart stage.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

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

AWS Big Data

DECEMBER 5, 2023

This dynamic tool, powered by AWS and CARTO, provided robust visualizations of which regions and populations were interacting with our survey, enabling us to zoom in quickly and address gaps in coverage. This cut down significantly on analytical turnaround times.

Measurement 85

Measurement Dashboards Data Warehouse Analytics 85

AWS Big Data

MARCH 1, 2023

Finding similar columns in a data lake has important applications in data cleaning and annotation, schema matching, data discovery, and analytics across multiple data sources. We include a code tutorial for you to deploy the resources to run the solution on sample data or your own data.

Data Lake 87

Data Lake Deep Learning Modeling Interactive 87

AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data. On the AWS Glue console, under ETL jobs in the navigation pane, choose Visual ETL. In the Create job section, choose Visual ETL.x

Data Quality 92

Data Quality Measurement Testing Visualization 92

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Corinium

JUNE 6, 2019

For instance, for a variety of reasons, in the short term, CDAOS are challenged with quantifying the benefits of analytics’ investments. Some of the work is very foundational, such as building an enterprise data lake and migrating it to the cloud, which enables other more direct value-added activities such as self-service.

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. As part of the transformation, the objects need to be treated to ensure data privacy (for example, PII redaction).

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

AWS Big Data

AUGUST 2, 2023

Using existing analytics tools such as Amazon Athena and Amazon QuickSight an organization can gain insight into its estimated carbon footprint. The data architecture diagram below shows an example of how you could use AWS services to calculate and visualize an organization’s estimated carbon footprint.

Data Lake 74

Data Lake Measurement Visualization Data Architecture 74

BizAcuity

MAY 16, 2022

The more effectively a company uses data, the better it performs. As a data analytics company, we have been observing a trend among certain large enterprises who are looking for real-time data streaming for analytics. Data mining. Visual Analytics and Data Visualization.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 98

Analytics Visualization Data Integration Cost-Benefit 98

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

Data Lake 79

Data Lake Testing Interactive Unstructured Data 79

AWS Big Data

NOVEMBER 30, 2023

With AWS Glue, you can discover and connect to more than 100 diverse data sources and manage your data in a centralized data catalog. You can visually create, run, and monitor extract, transform, and load (ETL) pipelines to load data into your data lakes. Choose Visual ETL.

IT 98

IT Visualization Machine Learning Data Integration 98

Jen Stirrup

MAY 5, 2020

Organizations need to recast storing their data. It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. You can also use Azure Data Lake storage as well, which is optimized for high-performance analytics.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

AWS Big Data

NOVEMBER 7, 2023

Now, as part of Infosys Cobalt and Infosys Topaz blueprints, enterprises can have near real-time analytics on transactional data, which can help them make informed decisions related to store management. This integration empowers users to go from data to predictions and visualizations faster than ever.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

MARCH 25, 2024

To understand the best ways to make API calls via Apache Flink, refer to Common streaming data enrichment patterns in Amazon Kinesis Data Analytics for Apache Flink. OpenSearch Service offers visualization capabilities powered by OpenSearch Dashboards and Kibana (1.5

Data Lake 92

Data Lake Unstructured Data Management Modeling 92