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. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Cloudera

JULY 21, 2022

As creators and experts in Apache Druid, Rill understands the data store’s importance as the engine for real-time, highly interactive analytics. Cloudera Data Warehouse and Rill Data—built on Apache Hive and Druid, respectively—can be connected using the Hive-Druid Integration. Cloudera Data Warehouse).

Metrics 85

Metrics Slice and Dice Data Warehouse Dashboards 85

AWS Big Data

NOVEMBER 9, 2023

It does this by helping teams handle the T in ETL (extract, transform, and load) processes. It allows users to write data transformation code, run it, and test the output, all within the framework it provides. As part of their cloud modernization initiative, they sought to migrate and modernize their legacy data platform.

Data Warehouse 107

Data Warehouse Testing Data Quality Reporting 107

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 141

Data Warehouse Digital Transformation Data-driven Reporting 141

AWS Big Data

SEPTEMBER 19, 2023

However, our legacy data warehouse-based solution was not equipped for this challenge. However, with a minimum data freshness of 10 minutes, this architecture inherently didn’t align with the near real-time fraud detection use case. He enjoys being at the intersection of big data and programming language theory.

Analytics 81

Analytics Risk Big Data Machine Learning 81

FineReport

APRIL 21, 2024

In today’s data-driven landscape, businesses are constantly seeking innovative solutions to harness the power of analytics effectively. Embedded BI tools have emerged as a transformative force, seamlessly integrating analytical capabilities directly into existing software applications.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 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 76

Data Analytics Analytics IoT Data Lake 76

Jet Global

MAY 1, 2023

Introduction Why should I read the definitive guide to embedded analytics? But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. The Definitive Guide to Embedded Analytics is designed to answer any and all questions you have about the topic.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

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.

Management 83

Management Data Warehouse Digital Transformation Dashboards 83

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 87

Enterprise Data Warehouse Data Lake Optimization 87

AWS Big Data

MARCH 16, 2023

Amazon Redshift is a fully managed data warehouse service that tens of thousands of customers use to manage analytics at scale. Together with price-performance , Amazon Redshift enables you to use your data to acquire new insights for your business and customers while keeping costs low.

Data Warehouse 52

Data Warehouse Testing Snapshot Modeling 52

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. Industry-wide, the positive ROI on quality data is well understood. 4 – Data Reporting. With a shocking 2.5

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

APRIL 24, 2024

In the rapidly-evolving world of embedded analytics and business intelligence, one important question has emerged at the forefront: How can you leverage artificial intelligence (AI) to enhance your data analysis? How does AI impact analytics and how do you get started? Forget the one-size-fits-all approach.

Business Intelligence 52

Business Intelligence Dashboards Software Reporting 52

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. We find it helpful to think of data operations as a factory. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines.

Testing 152

Testing Dashboards Measurement Experimentation 152

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 73

Risk Modeling Management Metadata 73

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 86

Data Lake Data Architecture Metadata Data Warehouse 86

Sisense

MARCH 30, 2021

In Gartner’s Top 10 Data and Analytics Trends for 2021, trend No. 9 is “dashboards will be replaced with automated, conversational, mobile, and dynamically generated insights customized to a user’s needs and delivered to their point of consumption.” for a custom, integrated embedded analytics solution.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

Jet Global

JULY 19, 2023

This is especially true with our embedded analytics offering, Logi Symphony, where we regularly solicit feedback through insightsoftware’s customer community. Let’s explore some of the latest enhancements and how they improve our industry-leading embedded analytics solution. Here’s how it works.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

Jet Global

OCTOBER 30, 2023

CXO Dashboards Meet Power BI to Turn Static Data Into Dynamic Insights A recent survey by insightsoftware reported that 89% of organizations feel they are not getting high-value data insights from their EPM. Together, CXO and Power BI provide you with access to insights from both EPM and BI data in one tool.

Dashboards 52

Dashboards Reporting Operational Reporting Software 52

Cloudera

NOVEMBER 29, 2021

Data transforms businesses. That’s where the data lifecycle comes into play. Managing data and its flow, from the edge to the cloud, is one of the most important tasks in the process of gaining data intelligence. . The firm also worked on creating a solid pipeline from the data warehouse to the data lake.

Data Lake 77

Data Lake Data Warehouse Data Architecture Reporting 77

AWS Big Data

MARCH 3, 2023

In this post, we share how the AWS Data Lab helped Tricentis to improve their software as a service (SaaS) Tricentis Analytics platform with insights powered by Amazon Redshift. While aggregating, summarizing, and aligning to a common information model, all transformations must not affect the integrity of data from its source.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

MARCH 15, 2023

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 68

Cost-Benefit Data Processing Optimization Data-driven 68

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting.

Reporting 52

Reporting Finance Data Quality Sales 52

Jet Global

AUGUST 24, 2023

It streamlines data integration, ensures real-time access to accurate information, enhances collaboration, and provides the flexibility needed to adapt to evolving ERP systems and business requirements. Data transformation ensures that the data aligns with the requirements of the new cloud ERP system.

Finance 52

Finance Reporting Data Integration Risk 52

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. But this was only the tip of the analytics iceberg.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 72

Reporting Metrics Optimization Data Lake 72

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 86

Data Lake Dashboards Metrics Metadata 86

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

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Bindu Chandramohan, Lead, Data Analytics, Alation : Thanks, Jason!

Metrics 52

Metrics Dashboards Sales Reporting 52

IBM Big Data Hub

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 91

Data Warehouse Data Lake Optimization Data-driven 91