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. They prevent you from drowning in data. The data warehouse.

Business Intelligence 270

Business Intelligence Dashboards Data Warehouse Sales 270

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

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 112

Cost-Benefit Enterprise ROI Data Warehouse 112

Laminar Security

APRIL 18, 2023

“Clearly organizations are needing a more scalable, sustainable approach to discovering and governing cloud data.” To achieve comprehensive large enterprise cloud data management, a DSPM must include summarized global data risk reporting as well as drilled-down views based on data sensitivity, security posture or other factors.

Enterprise 52

Enterprise Management Dashboards Snapshot 52

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

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 64

Modeling Data Warehouse Machine Learning Testing 64

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

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

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 66

Analytics Data Warehouse Data Lake Data-driven 66

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

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

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 Quality 69

Data Quality Data Warehouse Business Intelligence Data Governance 69

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

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

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

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

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

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The main challenges were risk mitigation and agility in analytics.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

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 56

Data Warehouse Data Lake Unstructured Data Optimization 56

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

datapine

JANUARY 24, 2021

If nothing can be changed, there is no point of analyzing data. But if you find a development opportunity, and see that your business performance can be significantly improved, then a KPI dashboard software could be a smart investment to monitor your key performance indicators and provide a transparent overview of your company’s data.

IT 317

IT Statistics KPI Data-driven 317

Octopai

JANUARY 8, 2020

Octopai’s metadata discovery and management suite provides visualization tools that empower you to see and report everything about sensitive customer data. You can evaluate and mitigate compliance risks. On the Horizon: Federal Data Privacy Law. Not Yet CCPA Compliant? In December 2019 a bill was introduced in the U.S.

Metadata 54

Metadata Key Performance Indicator OLAP Forecasting 54

Timo Elliott

OCTOBER 3, 2019

And because if companies or IT departments don’t implement them, they risk losing their roles to someone who will! Karsten Ruf , in turn, took the audience through the detailed SAP roadmap around BW4/HANA V2 and the brand-new SAP Data Warehouse cloud. People, collaboration, and ease of use.

Data Warehouse 63

Data Warehouse Digital Transformation Machine Learning Strategy 63

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 Cost-Benefit Metrics 40

Jet Global

JANUARY 15, 2020

For example, digging into a variance issue on a BI dashboard is impossible, because it requires drilling from summary data right into the transactional detail, to examine journal entries or subledger transactions. This introduces the risk of human error resulting in other business users basing their decisions on inaccurate data.

IT 59

IT Finance Reporting Data-driven 59

Jet Global

DECEMBER 23, 2020

On the way there, however, there is a great deal that business leaders can do to rein in costs, reduce risks, and increase the value that ultimately comes out of ERP system upgrades. Jet Analytics works with Power BI just as it does with Microsoft D365 BC, providing ease of use via a common data source for all dashboards.

Cost-Benefit 52

Cost-Benefit Data Warehouse Reporting Recreation/Entertainment 52

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

Sisense

APRIL 24, 2019

In organizations that operate without a data warehouse or separate analytical database for reporting, the only source of the latest and up-to-date data may be in the live production database. Taxing the production database for exploratory or duplicative reports is an unnecessary risk. Focusing on business outcomes.

Sales 111

Sales Optimization Data Warehouse Reporting 111

Birst BI

NOVEMBER 20, 2018

After a few iterations, this results in a well-defined business question with identifiable supporting data. A foundational data analysis tool is Statistics , and everyone intuitively applies it daily. A stock-out of an item may put a patient’s health at risk, but keeping huge amounts of inventory is very costly.

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

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 66

Data Warehouse Cost-Benefit KPI Risk 66

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 99

Data Warehouse Data Lake Analytics Machine Learning 99

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 58

Data Warehouse Unstructured Data Analytics Visualization 58

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 89

Data Analytics Analytics Data Warehouse Data Lake 89

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

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 176

Testing Data Quality Predictive Modeling Metrics 176

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. dashboards), it can leave your consumers frustrated with their experience. So let’s dive in! OLTP vs OLAP. Cluster Performance Configurations.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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