AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. Take the case of mobile gaming company Playrix.

Data Warehouse 59

Data Warehouse Data Lake Unstructured Data Optimization 59

Jet Global

JANUARY 5, 2021

Many AX customers have invested heavily in data warehouse solutions or in robust Power BI implementations that produce considerably more powerful reports and dashboards. As we have noted elsewhere , Power BI is still a relatively new platform, and it is heavily focused on dashboard analytics.

Reporting 98

Reporting Data Warehouse Finance Dashboards 98

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 121

Data Warehouse Analytics Data Lake Machine Learning 121

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. Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business.

Data Quality 241

Data Quality Metrics Data-driven Management 241

datapine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. In a slightly more technically-driven role, a BI developer is responsible for building, creating, or improving BI-driven solutions that help analysts transform data into knowledge, including data dashboards.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

AWS Big Data

AUGUST 1, 2024

Large-scale data warehouse migration to the cloud is a complex and challenging endeavor that many organizations undertake to modernize their data infrastructure, enhance data management capabilities, and unlock new business opportunities. This makes sure the new data platform can meet current and future business goals.

Data Warehouse 107

Data Warehouse KPI Optimization Cost-Benefit 107

CIO Business Intelligence

OCTOBER 19, 2023

With Power BI, you can pull data from almost any data source and create dashboards that track the metrics you care about the most. You can drill into data, create a variety of visualizations, and (literally) ask questions about it using AI.

Slice and Dice 126

Slice and Dice Scorecard Metrics Visualization 126

Cloudera

NOVEMBER 25, 2020

How could Matthew serve all this data, together , in an easily consumable way, without losing focus on his core business: finding a cure for cancer. The Vision of a Discovery Data Warehouse. A Discovery Data Warehouse is cloud-agnostic. Access to valuable data should not be hindered by the technology.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

Cloudera

JANUARY 21, 2021

While cloud-native, point-solution data warehouse services may serve your immediate business needs, there are dangers to the corporation as a whole when you do your own IT this way. And you also already know siloed data is costly, as that means it will be much tougher to derive novel insights from all of your data by joining data sets.

Data Warehouse 94

Data Warehouse Data Lake IT Analytics 94

Cloudera

OCTOBER 4, 2023

In telecommunications, fast-moving data is essential when we’re looking to optimize the network, improving quality, user satisfaction, and overall efficiency. In financial services, fast-moving data is critical for real-time risk and threat assessments. Kudu has this covered. appeared first on Cloudera Blog.

Data Warehouse 89

Data Warehouse Experimentation Cost-Benefit Dashboards 89

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

Sisense

JUNE 8, 2020

Datasets are on the rise and most of that data is on the cloud. The recent rise of cloud data warehouses like Snowflake means businesses can better leverage all their data using Sisense seamlessly with products like the Snowflake Cloud Data Platform to strengthen their businesses.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

DataKitchen

SEPTEMBER 21, 2023

Data in Place refers to the organized structuring and storage of data within a specific storage medium, be it a database, bucket store, files, or other storage platforms. In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

Alation

SEPTEMBER 7, 2021

In this blog we will discuss how Alation helps minimize risk with active data governance. Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. Two problems arise.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

FineReport

MAY 31, 2023

In today’s dynamic business environment, gaining comprehensive visibility into financial data is crucial for making informed decisions. This is where the significance of a financial dashboard shines through. What is A Financial Dashboard? You can download FineReport for free and have a try!

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

IBM Big Data Hub

MAY 9, 2023

With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. A data store built on open lakehouse architecture, it runs both on premises and across multi-cloud environments. Put AI to work in your business with IBM today IBM is infusing watsonx.ai

Data Warehouse 106

Data Warehouse Machine Learning Cost-Benefit Metadata 106

FineReport

APRIL 11, 2023

With the advent of Business Intelligence Dashboard (BI Dashboard), access to information is no longer limited to IT departments. Every user can now create interactive reports and utilize data visualization to disseminate knowledge to both internal and external stakeholders.

Dashboards 40

Dashboards Business Intelligence Metrics Cost-Benefit 40

Sisense

MARCH 27, 2019

To provide real-time data, these platforms use smart data storage solutions such as Redshift data warehouses , visualizations, and ad hoc analytics tools. This allows dashboards to show both real-time and historic data in a holistic way. What are the Real-Time BI Best Practices?

Business Intelligence 74

Business Intelligence Data Warehouse Predictive Modeling Visualization 74

Sisense

JUNE 30, 2020

Simply put, data visualization means showing data in a visual format that makes insights easier to understand for human users. Data is usually visualized in a pictorial or graphical form such as charts, graphs, lists, maps, and comprehensive dashboards that combine these multiple formats.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

AWS Big Data

MAY 28, 2024

Welcome back to our exciting exploration of architectural patterns for real-time analytics with Amazon Kinesis Data Streams! The key to unlock the full potential of this real-time data lies in your ability to effectively make sense of it and transform it into actionable insights in real time.

IoT 111

IoT Analytics Dashboards Data-driven 111

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

IBM Big Data Hub

SEPTEMBER 27, 2023

The list of challenges is long: cloud attack surface sprawl, complex application environments, information overload from disparate tools, noise from false positives and low-risk events, just to name a few. You get near real-time visibility and insights from your ingested data.

Cost-Benefit 93

Cost-Benefit OLAP Dashboards Visualization 93

AWS Big Data

DECEMBER 8, 2023

More and more of FanDuel’s community of analysts and business users looked for comprehensive data solutions that centralized the data across the various arms of their business. Their individual, product-specific, and often on-premises data warehouses soon became obsolete.

Data Warehouse 84

Data Warehouse Cost-Benefit KPI Risk 84

Jet Global

DECEMBER 2, 2019

The risk of not clearly identifying and defining these: you’ll attempt to use the wrong tools for the job. Not only will this cost you mountains of wasted time, but you’re also in extreme danger of having the wrong data in front of you or giving it to someone else. A good example of this could be Cost of Goods Sold (COGs).

Business Intelligence 69

Business Intelligence Reporting OLAP Data Warehouse 69

Jet Global

DECEMBER 8, 2020

A full Power BI implementation is a large-scale project, and it carries similar risks. If you are considering using Power BI in your organization, here are some key points to keep in mind that impact project risk: 1. Power BI was designed to be a dashboard visualization tool. Power BI Without the Risk.

Finance 52

Finance Risk Reporting Software 52

CIO Business Intelligence

APRIL 12, 2023

Most current data architectures were designed for batch processing with analytics and machine learning models running on data warehouses and data lakes. In this article, I’ll share insights on aligning vision and leadership, as well as reducing complexity to make data actionable for delivering real-time AI solutions.

Machine Learning 145

Machine Learning Cost-Benefit Data-driven Strategy 145

Jet Global

FEBRUARY 5, 2019

states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. This poor data quality translates into an average of $15 million per year in a ripple effect of financial loss, missed opportunities, and high-risk decision making. Because bad data is the reason behind poor analytics. .

Data Warehouse 69

Data Warehouse Data Quality Business Intelligence Data Governance 69

IBM Big Data Hub

NOVEMBER 6, 2023

Data-driven personalization is essential in today’s business environment. With 89% of digital businesses investing in personalization to enhance the customer digital experience , those that fail to do so risk falling behind. Watsonx.data allows enterprises to centrally gather, categorize and filter data from multiple sources.

Cost-Benefit 101

Cost-Benefit Enterprise Data Warehouse Testing 101

Jet Global

OCTOBER 7, 2020

For anyone that needs to develop custom reports and dashboards, it all begins with understanding data entities. What Are Data Entities? Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities.

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

JULY 29, 2020

There is a significant risk with unsupported products. Fear of the unknown has left many companies afraid to implement a new reporting tool, yet the risk of staying with Discoverer is becoming increasingly high. OBIEE is a strategic BI tool that provides a web platform with attractive dashboards suitable for C-level needs.

Reporting 98

Reporting Cost-Benefit Consulting Finance 98

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 78

Data Warehouse Data Lake Cost-Benefit Metadata 78

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

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. You can send data from your streaming source to this resource for ingesting the data into a Redshift data warehouse.

Data Analytics 113

Data Analytics Analytics Data Warehouse Data Lake 113

AWS Big Data

JUNE 28, 2023

In case the data sources change, data engineers have to manually make changes in their code and deploy it again. Furthermore, the time required to build or change pipelines makes the data unfit for near-real-time use cases such as detecting fraudulent transactions, placing online ads, and tracking passenger train schedules.

Analytics 84

Analytics Data Warehouse Data Lake Data-driven 84

Jet Global

APRIL 20, 2020

First, accounting moved into the digital age and made it possible for data to be processed and summarized more efficiently. Spreadsheets enabled finance professionals to access data faster and to crunch the numbers with much greater ease. Today’s technology takes this evolution a step further.

Business Intelligence 78

Business Intelligence Finance Data Warehouse OLAP 78

Birst BI

OCTOBER 30, 2018

Every day, these companies pose questions such as: Will this new client provide a good return on investment, relative to the potential risk? Is this existing client a termination risk? A well-designed credit scoring algorithm will properly predict both the low- and high-risk customers. Add the predictive logic to the data model.

Predictive Analytics 73

Predictive Analytics Descriptive Analytics Analytics Metrics 73

Jet Global

MAY 1, 2020

In Gartner’s report, an analyst goes to great pains to say that there is “much more risk associated to non-technology issues than there is to deploying the infrastructure, tools, and apps.”. We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. Risk to the business.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64