Sisense

OCTOBER 30, 2019

A critical part of effectively exploring your data, transforming it into actionable insights, and enhancing decision-making for your business is being empowered to slice and dice your data, and be less dependent on technical resources for new updates. Analytics reports are a vital part of this process.

Data-driven 70

Data-driven Reporting Slice and Dice Management 70

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. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Analytics tell the story of markets and customers. Analytics enable companies to understand their environment. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

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. Did you know?

Big Data 275

Big Data Cost-Benefit Internet of Things Optimization 275

AWS Big Data

APRIL 11, 2023

Such a solution should use the latest technologies, including Internet of Things (IoT) sensors, cloud computing, and machine learning (ML), to provide accurate, timely, and actionable data. In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services.

Forecasting 76

Forecasting Management IoT Data-driven 76

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 90

Metadata Data Lake Visualization Data Transformation 90

CIO Business Intelligence

JANUARY 24, 2024

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

Cloudera

APRIL 19, 2022

Data holds incredible untapped potential for Australian organisations across industries, regardless of individual business goals, and all organisations are at different points in their data transformation journey with some achieving success faster than others. . More importantly, effective data strategies don’t stand still.

Data-driven 90

Data-driven Data Strategy Strategy Big Data 90

InsightOut

MAY 4, 2021

In this data-driven world, building a team of data analysts can be a challenge. Implementing data visualization and analytics dashboards can be the beginning of the data transformation journey.

Visualization 52

Visualization Dashboards Data-driven Data Transformation 52

AWS Big Data

APRIL 26, 2023

Additionally, this forecasting system needs to provide data enrichment steps including byproducts, serve as the master data around the semiconductor management, and enable further use cases at the BMW Group. To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub.

Manufacturing 122

Manufacturing Forecasting Data Lake Big Data 122

AWS Big Data

APRIL 19, 2023

Data mesh is a new approach to data management. Companies across industries are using a data mesh to decentralize data management to improve data agility and get value from data. This is especially true in a large enterprise with thousands of data products.

Technology 84

Technology Data-driven Machine Learning Sales 84

Smart Data Collective

APRIL 29, 2020

As the world is gradually becoming more dependent on data, the services, tools and infrastructure are all the more important for businesses in every sector. Data management has become a fundamental business concern, and especially for businesses that are going through a digital transformation. What is data management?

Management 84

Management Data Warehouse Digital Transformation Dashboards 84

erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. Tracing the source of data is an arduous task. With all these diverse data sources, and if systems are integrated, it is difficult to understand the complicated data web they form much less get a simple visual flow.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

Alation

FEBRUARY 20, 2020

REFLECTIONS FROM THE GARTNER BI & ANALYTICS SUMMIT I hate to admit that the last time I attended the Gartner BI & Analytics Summit, Howard Dresner was still the host. For me personally, it was an amazing return this year to the now appropriately re-named, Gartner BI & Analytics Summit held in Grapevine, Texas.

Scorecard 52

Scorecard ROI Data-driven Visualization 52

AWS Big Data

JUNE 6, 2023

Alerts and notifications play a crucial role in maintaining data quality because they facilitate prompt and efficient responses to any data quality issues that may arise within a dataset. It simplifies your experience of monitoring and evaluating the quality of your data.

Data Quality 75

Data Quality Metrics Data-driven Visualization 75

Sisense

MARCH 14, 2021

Attempting to learn more about the role of big data (here taken to datasets of high volume, velocity, and variety) within business intelligence today, can sometimes create more confusion than it alleviates, as vital terms are used interchangeably instead of distinctly. Big data challenges and solutions.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture. Don’t try to do everything at once!

Data Governance 85

Data Governance Business Objectives Strategy Data Quality 85

AWS Big Data

MAY 16, 2023

Different communication infrastructure types such as mesh network and cellular can be used to send load information on a pre-defined schedule or event data in real time to the backend servers residing in the utility UDN (Utility Data Network).

Dashboards 78

Dashboards Statistics Data Collection Business Intelligence 78

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. Data pipelines are composed of multiple steps with dependencies and triggers.

Snapshot 117

Snapshot Data-driven Optimization Management 117

Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. 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. What is data integrity? Data integrity risks.

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

AWS Big Data

OCTOBER 12, 2023

Amazon EMR Serverless provides a serverless runtime environment that simplifies the operation of analytics applications that use the latest open source frameworks, such as Apache Spark and Apache Hive. The integration between AWS Step Functions and Amazon EMR Serverless makes it easier to manage and orchestrate big data workflows.

Big Data 109

Big Data Data-driven Management Visualization 109

bridgei2i

NOVEMBER 17, 2020

But what is changing today, is the nature and shape of data powering these systems and processes. A variety of signals in the new digital world can be transformed into data to derive insights and learnings on how to improve process performance. Automation through technology had the same outcomes as the first wave though.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

Alation

FEBRUARY 2, 2023

Data product managers are in high demand these days. This makes it more important for aspiring data product managers to stay ahead of the competition. So what sets data product managers apart from the pack? This post will unpack the top 7 traits that successful data product managers have in common. Sounds exciting?

Management 52

Management Data-driven Visualization Strategy 52

Anmut

MARCH 24, 2022

A closer look at the importance (and transformational value) of your organisation’s data landscape. After decades in the background, data is currently king of the business world. Over 70% of digital transformations fail, and most CDOs last less than two-and-half years. What is a data landscape?

ROI 52

ROI Measurement Data-driven Data Transformation 52

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

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

Alation

MARCH 22, 2022

Data people face a challenge. They must put high-quality data into the hands of users as efficiently as possible. As the latest iteration in this pursuit of high-quality data sharing, DataOps combines a range of disciplines. It synthesizes all we’ve learned about agile, data quality , and ETL/ELT.

Metadata 52

Metadata Cost-Benefit Data Quality Data Lake 52

AWS Big Data

JANUARY 17, 2024

This allows you to simplify security and governance over transactional data lakes by providing access controls at table-, column-, and row-level permissions with your Apache Spark jobs. Many large enterprise companies seek to use their transactional data lake to gain insights and improve decision-making.

Data Lake 96

Data Lake Snapshot Big Data Data-driven 96

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 99

Analytics Visualization Data Integration Cost-Benefit 99

AWS Big Data

OCTOBER 11, 2023

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

Management 107

Management Metadata Analytics Dashboards 107

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

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. 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.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 67

Optimization Data Lake Cost-Benefit Reporting 67

Cloudera

MARCH 14, 2023

We just announced the general availability of Cloudera DataFlow Designer , bringing self-service data flow development to all CDP Public Cloud customers. In this blog post we will put these capabilities in context and dive deeper into how the built-in, end-to-end data flow life cycle enables self-service data pipeline development.

Testing 82

Testing Publishing Metadata Interactive 82

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 97

Dashboards Analytics Metadata Data Warehouse 97

DataKitchen

JULY 27, 2023

The Ten Standard Tools To Develop Data Pipelines In Microsoft Azure. While working in Azure with our customers, we have noticed several standard Azure tools people use to develop data pipelines and ETL or ELT processes. We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

DataRobot Blog

MARCH 10, 2022

These initiatives utilize interconnected devices and automated machines that create a hyperbolic increase in data volumes. This type of growth has stressed legacy data management systems and makes it nearly impossible to implement a profitable data-centered solution. High-level example of a common machine learning lifecycle.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52