CIO Business Intelligence

JANUARY 19, 2024

Whether you’re looking to earn a certification from an accredited university, gain experience as a new grad, hone vendor-specific skills, or demonstrate your knowledge of data analytics, the following certifications (presented in alphabetical order) will work for you. Not finding what you’re looking for?

Data Science 126

Data Science Machine Learning Predictive Modeling Experimentation 126

Analytics Vidhya

MAY 13, 2024

However, the traditional Transformer architecture has limitations when it comes to specific types of […] The post A Comprehensive Guide on i-Transformer appeared first on Analytics Vidhya.

Machine Learning 264

Machine Learning Analytics IT Forecasting 264

CIO Business Intelligence

FEBRUARY 16, 2023

“All they would have to do is just build their model and run with it,” he says. But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. For now, it operates under a centralized “hub and spokes” model.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

AWS Big Data

APRIL 11, 2023

In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services. Finally, we can use Amazon SageMaker to build forecasting models that can predict inventory demand and optimize stock levels.

Forecasting 78

Forecasting Management IoT Data-driven 78

CIO Business Intelligence

JANUARY 24, 2024

Building a successful data strategy at scale goes beyond collecting and analyzing data,” says Ryan Swann, chief data analytics officer at financial services firm Vanguard. When different departments, business units, or groups keep data stored in systems not available to others, it diminishes the value of the data.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. One of the key benefits of DataOps is the ability to accelerate the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

IBM Big Data Hub

APRIL 14, 2023

To meet their specific needs, the experts at 1Direction Global, comprised of certified accountants and engineers, turned to IBM Planning Analytics for Watson, a flexible and powerful planning and analysis tool. Additionally, dashboards and reports were crafted based on the budget models and conducted variance analysis for specific areas.

Forecasting 70

Forecasting Sales Dashboards Reporting 70

AWS Big Data

APRIL 26, 2023

For historic reasons, the required data for this aggregation step is siloed and represented differently in diverse systems. Because each source system and data type have its own schema and format, it’s particularly difficult to perform analytics based on this data.

Manufacturing 125

Manufacturing Forecasting Data Lake Big Data 125

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 110

Data Warehouse Testing Data Quality Reporting 110

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. Business/Data Analyst: The business analyst is all about the “meat and potatoes” of the business. 2 – Data profiling.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jen Stirrup

SEPTEMBER 30, 2021

Azure ML can become a part of the data ecosystem in an organization, but this requires a mindshift from working with Business Intelligence to more advanced analytics. How can we can adopt a mindshift from Business Intelligence to advanced analytics using Azure ML? Modelling Data.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

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. Rill solves this with pipeline services and Rill Developer, a free SQL-based data modeler. Cloudera Data Warehouse). Large-scale high throughput analytics.

Metrics 83

Metrics Slice and Dice Data Warehouse Dashboards 83

datapine

MAY 2, 2023

Table of Contents 1) Benefits Of Big Data In Logistics 2) 10 Big Data In Logistics Use Cases Big data is revolutionizing many fields of business, and logistics analytics is no exception. The complex and ever-evolving nature of logistics makes it an essential use case for big data applications.

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

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

Sisense

MARCH 30, 2021

In Gartner’s Top 10 Data and Analytics Trends for 2021, trend No. The Sisense Fusion platform embodies this idea, empowering every user to embrace analytics via actionable intelligence delivered directly to them where they spend their time. The Sisense Q1 2021 release is focused on bringing customized analytics to each person.

Dashboards 52

Dashboards Machine Learning Data Warehouse Marketing 52

BizAcuity

APRIL 1, 2023

Introduction Data fuels today’s business and Microsoft’s Power BI tool helps you make sense of that data. Power BI is a suite of business analytics tools to analyze data and share insights. Especially when handling large data volumes, it becomes important to optimize the way data is loaded to the data models and storage.

Optimization 52

Optimization Dashboards Sales Modeling 52

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines. Where are the data engineers, scientists and analytics?

Testing 152

Testing Dashboards Measurement Experimentation 152

Sisense

OCTOBER 15, 2020

Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. Streaming data analytics is expected to grow into a $38.6 The first step is to navigate to the “Data” tab and create a new live model.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

Cloudera

OCTOBER 13, 2020

Machine Learning – has grown from a collaborative workbench to an end-to-end Production ML platform that enables data scientists to deploy a model or an application to production in minutes with production-level monitoring, governance and performance tracking. Enrich – Data Engineering (Apache Spark and Apache Hive).

Data Warehouse 91

Data Warehouse Machine Learning Visualization Data Lake 91

BizAcuity

SEPTEMBER 21, 2022

Data fuels today’s business and Microsoft’s Power BI tool helps you make sense of that data. Power BI is a suite of business analytics tools to analyze data and share insights. But with a Power BI Premium license, you get to store BI assets on-premises and receive a 50 GB cap on dataset size and up to 100 TB data storage.

Optimization 52

Optimization Dashboards Sales Modeling 52

Sisense

MARCH 14, 2021

However, when investigating big data from the perspective of computer science research, we happily discover much clearer use of this cluster of confusing concepts. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Cloudera

AUGUST 3, 2022

The challenges of arbitrary code execution notwithstanding, there have been attempts to provide a stronger security model but with mixed results. Customers will now get the same consistent view of their data with the analytic processing engine of their choice without any compromises. .

Snapshot 84

Snapshot Cost-Benefit Machine Learning Data Transformation 84

CIO Business Intelligence

JUNE 13, 2022

According to Evanta’s 2022 CIO Leadership Perspectives study, CIOs’ second top priority within the IT function is around data and analytics, with CIOs seeing advancing organizational use of data as key to reaching enterprise objectives. Angel-Johnson shares that perspective. “I Colisto says he’s seizing on those opportunities.

IT 144

IT Digital Transformation Strategy Internet of Things 144

CIO Business Intelligence

OCTOBER 18, 2022

“In the old stadium, we just didn’t have the ability to get the data that we needed,” says Machelle Noel, manager of analytic systems at the Texas Rangers Baseball Club. Analytics, Data Management Some of our systems were old. We just didn’t have the ability that we now have in this new, state-of-the-art facility.”.

Data Transformation 141

Data Transformation Consulting Data Lake Reporting 141

DataRobot Blog

MARCH 10, 2022

By enabling data scientists to rapidly iterate through model development, validation, and deployment, DataRobot provides the tools to blitz through steps four and five of the machine learning lifecycle with AutoML and Auto Time-Series capabilities. Train, Compare, Rank, Validate, and Select Models for Production.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

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

CDW Research Hub

OCTOBER 25, 2019

As we review data transformation and modernization strategies with our clients, we find many are investigating Snowflake as a data warehouse solution due to its ease of use, speed, and increased flexibility over a traditional data warehouse offering. Analytics and intelligence for business users and user adoption.

Data Warehouse 40

Data Warehouse Testing Strategy Data-driven 40

CIO Business Intelligence

JUNE 29, 2022

Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Cloudera

DECEMBER 21, 2021

Cloudera’s Shared Data Experience (SDX) provides all these capabilities allowing seamless data sharing across all the Data Services including CDE. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. . CDP Airflow Operators.

Snapshot 115

Snapshot Data-driven Optimization Management 115

Ontotext

NOVEMBER 18, 2021

Picture this – you start with the perfect use case for your data analytics product. And all of them are asking hard questions: “Can you integrate my data, with my particular format?”, “How well can you scale?”, “How many visualizations do you offer?”. Nowadays, data analytics doesn’t exist on its own.

Visualization 98

Visualization Reporting Metadata Enterprise 98

Ontotext

MARCH 20, 2024

Unleashing the Power of Data Connections Zenia Graph isn’t just another data solution company. We are pioneers in knowledge graphs – a revolutionary technology that goes beyond simple data analytics, aggregation, and reporting. Zenia Graph’s Salesforce Accelerator makes this a reality.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

AWS Big Data

APRIL 19, 2023

A knowledge graph allows us to combine data from different sources to gain a better understanding of a specific problem domain. In Neptune, we combine the Customer product data with an additional data product: Sales Opportunity. With the AWS SDK for Pandas, we combine this data by running a query against the Neptune graph.

Technology 86

Technology Data-driven Machine Learning Sales 86

AWS Big Data

NOVEMBER 15, 2023

BMW Cloud Efficiency Analytics (CLEA) is a homegrown tool developed within the BMW FinOps CoE (Center of Excellence) aiming to optimize and reduce costs across all these accounts. In this post, we explore how the BMW Group FinOps CoE implemented their Cloud Efficiency Analytics tool (CLEA), powered by Amazon QuickSight and Amazon Athena.

Dashboards 99

Dashboards Analytics Metadata Data Warehouse 99

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Cloudera

JUNE 1, 2021

This means we can double down on our strategy – continuing to win the Hybrid Data Cloud battle in the IT department AND building new, easy-to-use cloud solutions for the line of business. It also means we can complete our business transformation with the systems, processes and people that support a new operating model. .

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

Data Insight

NOVEMBER 7, 2019

Analytics in an agile organisation Data Insight’s very first DI Day welcomed an array of inspiring speakers. One of the members of our ‘Leaders in Data Transformation’ panel, Alex Tran, shared the lessons learnt on working Agile, a hot topic in organisations today.

Data Transformation 40

Data Transformation Modeling Management IT 40

CIO Business Intelligence

DECEMBER 22, 2022

DataOps (data operations) is an agile, process-oriented methodology for developing and delivering analytics. It brings together DevOps teams with data engineers and data scientists to provide the tools, processes, and organizational structures to support the data-focused enterprise. What is DataOps?

Analytics 130

Analytics Machine Learning Software Data Quality 130