FineReport

MAY 31, 2023

There are also some other key challenges that will often be encountered during the process of creating financial dashboards: Data Integration : One of the primary challenges is integrating data from various sources. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. It works in Salesforce just like any other native Salesforce data,” Carlson said.

Data Integration 114

Data Integration Data Lake Metadata Data Warehouse 114

CIO Business Intelligence

OCTOBER 26, 2023

This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 127

Business Intelligence Data-driven Statistics Data Warehouse 127

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog. She helps customers architect data analytics solutions at scale on AWS.

Measurement 79

Measurement Dashboards Data Warehouse Analytics 79

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 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

Cloudera

MAY 10, 2021

The introduction of CDP Public Cloud has dramatically reduced the time in which you can be up and running with Cloudera’s latest technologies, be it with containerised Data Warehouse , Machine Learning , Operational Database or Data Engineering experiences or the multi-purpose VM-based Data Hub style of deployment.

Data Warehouse 104

Data Warehouse Consulting Machine Learning Risk 104

CIO Business Intelligence

MARCH 6, 2024

This was a gift because it forced us into data governance and we sell data governance products, so this wasn’t a new concept to us. The definition of ARR, for example, required debate between the CFO and the CEO, and then my team built the definition into the data warehouse.

Modeling 114

Modeling Management IT Metrics 114

Cloudera

SEPTEMBER 29, 2022

In the data fabric implementation, the concepts in data mesh map to real-world artifacts in a data architecture. Corresponding to the data mesh example in Figure 4, D1, D2 are tables in a data warehouse. A2 is an app built as a spark job orchestrated to run when some data shows up.

Data Architecture 74

Data Architecture Metadata Data Warehouse Sales 74

KDnuggets

JANUARY 16, 2020

Whereas a data warehouse will need rigid data modeling and definitions, a data lake can store different types and shapes of data. In a data lake, the schema of the data can be inferred when it’s read, providing the aforementioned flexibility.

Data Lake 67

Data Lake Data Warehouse Modeling 67

CIO Business Intelligence

MARCH 16, 2022

In the same way there is no universally accepted definition for ‘digital’ either. The same goes for the adoption of data warehouse and business intelligence. The telecom sector prepares the data warehouse and business intelligence use cases even before they go live with their first customer.

Technology 107

Technology Digital Transformation Business Intelligence Data Warehouse 107

datapine

SEPTEMBER 27, 2022

Definitely, one of the best books for SQL beginners! 3) “Practical SQL: A Beginner’s Guide to Storytelling with Data” by Anthony DeBarros. Analyze data as a pro, even if you are a beginner” is the premise of the book by journalist and data scientist, Anthony DeBarros. stars rating on Amazon so far.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

CIO Business Intelligence

OCTOBER 19, 2023

Disparate data sources Data from different sources comes in multiple formats, such as Excel, JSON, CSV, etc., For example, two data sources may have different data types of the same field or different definitions for the same partner data. or databases such as Oracle, MongoDB, MySQL, etc.

Data Integration 126

Data Integration Unstructured Data Data-driven Data Warehouse 126

Paul Blogs on BI

SEPTEMBER 8, 2021

While we have definitely seen an acceleration in organizations using or moving operational applications to the cloud, Business Intelligence has lagged behind. It therefore makes sense when they move their data warehouses and BusinessObjects to move them to their existing private cloud.

Data Warehouse 59

Data Warehouse Data Processing Data Lake Testing 59

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Also, the data lake layer is not limited to cloud object stores.

Unstructured Data 61

Unstructured Data Data Lake Data Warehouse Machine Learning 61

Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

Timo Elliott

MAY 27, 2022

I was at the Gartner Data & Analytics conference in London a couple of weeks ago and I’d like to share some thoughts on what I think was interesting, and what I think I learned…. First, data is by default, and by definition, a liability , because it costs money and has risks associated with it.

Data Analytics 123

Data Analytics Analytics Recreation/Entertainment Data Lake 123

CIO Business Intelligence

NOVEMBER 14, 2022

Decision support systems definition A decision support system (DSS) is an interactive information system that analyzes large volumes of data for informing business decisions. A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. DSS software system.

Data mining 137

Data mining Data-driven Statistics OLAP 137

AWS Big Data

NOVEMBER 17, 2023

Seeds – These are CSV files in your dbt project (typically in your seeds directory), which dbt can load into your data warehouse using the dbt seed command. After you create the cluster, create an ECS task and assign the created dbt image as the task definition family. These SCDs identify how a row in a table changes over time.

Snapshot 87

Snapshot Data Processing Testing Data Warehouse 87

erwin

AUGUST 15, 2022

I was pricing for a data warehousing project with just 4 TBs of data, small by today’s standards. I chose “ON Demand” for up to 64 virtual CPUs and 448 GB of memory since I wanted this data warehouse to fit entirely, or at least mostly, within memory. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. To get started, we need an Amazon Redshift Serverless data warehouse with the Redshift ML feature enabled and an Amazon SageMaker Studio environment with access to SageMaker Feature Store.

Modeling 62

Modeling Data Warehouse Machine Learning Testing 62

Cloudera

JANUARY 19, 2024

This can include assumptions about the intent of the natural language used, like the definition of “top selling products,” values of needed literals, and how joins can be created. Log in to the Cloudera Data Warehouse service as DWAdmin. Log in to the data warehouse service as DWAdmin.

Data Warehouse 72

Data Warehouse Data Processing Optimization Modeling 72

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g.,

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

AWS Big Data

AUGUST 31, 2023

One of the major and essential parts in a data warehouse is the extract, transform, and load (ETL) process which extracts the data from different sources, applies business rules and aggregations and then makes the transformed data available for the business users. manifest' s3.Bucket(bucketname).put_object(Key=keypath,

Data Warehouse 79

Data Warehouse Data-driven Testing Business Intelligence 79

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. When is a Task “Done”.

Testing 157

Testing Dashboards Measurement Experimentation 157

datapine

MAY 9, 2019

Business intelligence concepts refer to the usage of digital computing technologies in the form of data warehouses, analytics and visualization with the aim of identifying and analyzing essential business-based data to generate new, actionable corporate insights. The data warehouse. 1) The raw data.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

Birst BI

JANUARY 23, 2018

Many IT and data management professionals posit that a single central data repository, such as a large cloud data warehouse or a data lake, is the definitive “single version of the truth.” For example, the definition of “profit” can be quite complex. Connecting definitions to underlying data.

Data Warehouse 50

Data Warehouse Data Governance Data Lake Enterprise 50

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 80

Data Lake Data Architecture Data-driven Data Warehouse 80

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse 69

Data Warehouse Cost-Benefit Data Governance Data-driven 69

Cloudera

OCTOBER 6, 2022

Everyone has their own ideas about what digital transformation means, so I decided to look up a few definitions. . In reflecting on these definitions, I particularly like how Gartner highlights legacy modernization as a common component of such initiatives, noting that digital transformation can be more about digitization than transformation.

Digital Transformation 86

Digital Transformation Cost-Benefit Data Lake Machine Learning 86

FineReport

JULY 16, 2021

When we talk about business intelligence system, it normally includes the following components: data warehouse BI software Users with appropriate analytical. Data analysis and processing can be carried out while ensuring the correctness of data. Data Warehouse. Data Analysis. INTERFACE OF BI SYSTEM.

Business Intelligence 98

Business Intelligence Informatics Data Warehouse Data mining 98

Alation

DECEMBER 21, 2022

MDM is a discipline that helps organize critical information to avoid duplication, inconsistency, and other data quality issues. Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management.

Management 52

Management Data Quality Metadata Testing 52

FineReport

JULY 28, 2021

If you are curious about the difference and similarities between them, this article will unveil the mystery of business intelligence vs. data science vs. data analytics. Definition: BI vs Data Science vs Data Analytics. Photo by Chris Ried on Unsplash. What is Business Intelligence?

Business Intelligence 98

Business Intelligence Data Science Data Analytics Analytics 98

datapine

SEPTEMBER 29, 2022

Reporting being part of an effective DQM, we will also go through some data quality metrics examples you can use to assess your efforts in the matter. But first, let’s define what data quality actually is. What is the definition of data quality? Industry-wide, the positive ROI on quality data is well understood.

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

NOVEMBER 20, 2023

His team focuses on building distributed systems to enable customers with interactive and simple to use interfaces to efficiently manage and transform petabytes of data seamlessly across data lakes on Amazon S3, databases and data-warehouses on cloud.

Metrics 92

Metrics Data Lake Cost-Benefit Dashboards 92

Jet Global

APRIL 10, 2019

Jet Analytics is a business intelligence and reporting solution with pre-built data warehouse and OLAP cubes for Dynamics GP. Multi Data Source Consolidation. Data Warehouse and OLAP Cubes. Option 3: Jet Analytics. Management Reporter. Jet Analytics. Dashboards and KPIs. Power Bi Integration. Advanced Security.

Reporting 75

Reporting Management OLAP Data Warehouse 75

BizAcuity

SEPTEMBER 5, 2019

But more importantly, from a business and strategic viewpoint, it means that casinos are capturing consumer data into data warehouses, at different points inside the casino – the same data that is crucial for a host of purposes. These systems are amassing information into independent data warehouses.

ROI 75

ROI Data Warehouse Advertising Data Processing 75

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73