Smart Data Collective

APRIL 2, 2019

Data Lakes are among the most complex and sophisticated data storage and processing facilities we have available to us today as human beings. Analytics Magazine notes that data lakes are among the most useful tools that an enterprise may have at its disposal when aiming to compete with competitors via innovation.

Data Lake 84

Data Lake Big Data OLAP Testing 84

Smart Data Collective

AUGUST 7, 2019

One study found that 77% of small businesses don’t even have a big data strategy. If your company lacks a big data strategy, then you need to start developing one today. The best thing that you can do is find some data analytics tools to solve your most pressing challenges. There are many benefits to data analytics.

Data Analytics 100

Data Analytics Analytics Big Data Data Lake 100

AWS Big Data

APRIL 24, 2023

Building a data lake on Amazon Simple Storage Service (Amazon S3) provides numerous benefits for an organization. However, many use cases, like performing change data capture (CDC) from an upstream relational database to an Amazon S3-based data lake, require handling data at a record level.

Data Lake 80

Data Lake Data Governance Cost-Benefit Machine Learning 80

Corinium

JUNE 6, 2019

Will you please describe your role at Fractal Analytics? Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers? Are you seeing currently any specific issues in the Insurance industry that should concern Chief Data & Analytics Officers?

Insurance 250

Insurance Analytics Forecasting Deep Learning 250

AWS Big Data

DECEMBER 21, 2023

As the volume and complexity of analytics workloads continue to grow, customers are looking for more efficient and cost-effective ways to ingest and analyse data. OpenSearch Service is used for multiple purposes, such as observability, search analytics, consolidation, cost savings, compliance, and integration.

Analytics 96

Analytics IT Data Lake Visualization 96

KDnuggets

JANUARY 18, 2023

7 Best Platforms to Practice SQL • Explainable AI: 10 Python Libraries for Demystifying Your Model's Decisions • ChatGPT: Everything You Need to Know • Data Lakes and SQL: A Match Made in Data Heaven • Google Data Analytics Certification Review for 2023

Data Lake 85

Data Lake Modeling Data Analytics Analytics 85

DataKitchen

AUGUST 3, 2021

First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. Second-generation – gigantic, complex data lake maintained by a specialized team drowning in technical debt. See the pattern?

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

DataKitchen

AUGUST 19, 2021

In figure 1 below, we see that the data requirements are quite different for each of three critical phases of a drug’s lifecycle: Table 1: Lifecycle phases of pharmaceutical product launch. Each distinct phase of the drug lifecycle requires a unique focus for analytics. Pharma Data Requirements. The new Recipes run, and BOOM!

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Sirius has created a lightweight development tool to rapidly build and deploy best-practice data models.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 95

Data Governance Unstructured Data Metadata Data Lake 95

AWS Big Data

JUNE 6, 2023

As most organizations, that have turned to Google Analytics (GA) as a digital analytics solution, mature they discover a more pressing need to integrate this data silo with the rest of their organization’s data to enable better analytics and resulting product development and fraud detection.

Analytics 55

Analytics Data Lake Testing Optimization 55

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

CIO Business Intelligence

DECEMBER 6, 2023

The migration, still in its early stages, is being designed to benefit from the learned efficiencies, proven sustainability strategies, and advances in data and analytics on the AWS platform over the past decade. Here, Dickson sees data generated from its industrial machines being very productive.

Manufacturing 74

Manufacturing Data Lake Digital Transformation Machine Learning 74

Andrew White

DECEMBER 9, 2019

The client had recently engaged with a well-known consulting company that had recommended a large data catalog effort to collect all enterprise metadata to help identify all data and business issues. Through the use of AI and ML, these new catalogs would find all the data and create a new data model much more quickly then before.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

CIO Business Intelligence

MARCH 18, 2024

Data replication and synchronization also plays a role in reducing costs—solutions like Rocket® Data Replicate and Sync allow any changes to data to be fed directly into data lakes and warehouses, streamlining critical processes and enhancing overall analytical capabilities.

Cost-Benefit 83

Cost-Benefit Data Lake Machine Learning Data Integration 83

BizAcuity

JULY 13, 2021

Garnering over more than 6 decades of gaming intelligence experience of our founding team and using advanced technologies like AI & machine learning have a custom-built gaming accelerator platform that provides both visualization and data analytics. Data Enrichment/Data Warehouse Layer. Data Analytics Layer.

Optimization 52

Optimization Marketing Analytics Data Warehouse 52

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

CIO Business Intelligence

DECEMBER 1, 2022

Tapped to guide the company’s digital journey, as she had for firms such as P&G and Adidas, Kanioura has roughly 1,000 data engineers, software engineers, and data scientists working on a “human-centered model” to transform PepsiCo into a next-generation company.

Digital Transformation 122

Digital Transformation IoT Data-driven KPI 122

AWS Big Data

APRIL 26, 2023

To enable this use case, we used the BMW Group’s cloud-native data platform called the Cloud Data Hub. In 2019, the BMW Group decided to re-architect and move its on-premises data lake to the AWS Cloud to enable data-driven innovation while scaling with the dynamic needs of the organization.

Forecasting 122

Forecasting Manufacturing Data Lake Big Data 122

Jen Stirrup

MAY 5, 2020

Organizations need to recast storing their data. It is more than just some giant USB stick in the sky that’s going to store all of the data. It has a lot of services that you can use, such as Big Data analytics. Using open-source analytics means you can spin up significant clusters as and when you need them.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

CIO Business Intelligence

MARCH 14, 2024

As businesses digitally transform, technology is increasingly integrated into every activity, and the CIO is becoming more of a catalyst for data-driven value creation through analytics, new AI model training, software development, automation, vendor engagement, and more. The first step in this transformation was organizational.

Digital Transformation 83

Digital Transformation Sales Forecasting Data Lake 83

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics.

Management 67

Management Data Lake Uncertainty Data Warehouse 67

FineReport

MARCH 24, 2024

Rapid technological advancements and extensive networking have propelled the evolution of data analytics, fundamentally reshaping decision-making practices across various sectors. In this landscape, data analysts assume a pivotal role, tasked with interpreting data to drive informed decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Sisense

JUNE 12, 2019

At Sisense, our mission is to empower users of all kinds with deep insights from even the most complex data. In addition, providing a world-class analytics platform requires a deep understanding of how to best leverage AI/ML to support the needs of all users from the novice to the most technical. From Data to Data-Powered Apps.

Analytics 75

Analytics Data-driven Dashboards IoT 75

AWS Big Data

JANUARY 30, 2023

Many customers need an ACID transaction (atomic, consistent, isolated, durable) data lake that can log change data capture (CDC) from operational data sources. There is also demand for merging real-time data into batch data. Delta Lake framework provides these two capabilities.

Insurance 79

Insurance Data Lake Data-driven Management 79

Cloudera

DECEMBER 19, 2018

Data analytics priorities have shifted this year. Don’t blink or you might miss what leading organizations are doing to modernize their analytic and data warehousing environments. Natural language analytics and streaming data analytics are emerging technologies that will impact the market.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

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. With Amazon Athena , retailers can analyze this data to identify trends, patterns, and anomalies, and use Amazon ElastiCache for customer-facing applications with reduced latency.

Forecasting 76

Forecasting Management IoT Data-driven 76

CIO Business Intelligence

SEPTEMBER 12, 2022

Fazal and his team have moved most of NJ Transit’s data to the cloud, evolving from simple reports to advanced analytics and AI/ML models that generate insights that transportation business analysts could only dream about in the past, he says. “We As a result, NJ Transit’s data maturity as an organization has grown.

Data Warehouse 116

Data Warehouse Predictive Analytics Data Lake IoT 116

CIO Business Intelligence

DECEMBER 13, 2022

Our digital transformation strategy is centered around establishing a consumer-oriented model that helps us customize chronic care management based on the ever-changing conditions of each patient.” Tim Scannell: How much of a role do technologies like data analytics and AI play in DaVita’s overall technology and business strategy?

Strategy 92

Strategy Technology Digital Transformation Data Lake 92

AWS Big Data

MARCH 2, 2023

Many organizations are building data lakes to store and analyze large volumes of structured, semi-structured, and unstructured data. In addition, many teams are moving towards a data mesh architecture, which requires them to expose their data sets as easily consumable data products.

Data Lake 76

Data Lake Testing Interactive Unstructured Data 76

Smart Data Collective

FEBRUARY 20, 2022

Whether it’s data management, analytics, or scalability, AWS can be the top-notch solution for any SaaS company. Data storage databases. Your SaaS company can store and protect any amount of data using Amazon Simple Storage Service (S3), which is ideal for data lakes, cloud-native applications, and mobile apps.

Cost-Benefit 116

Cost-Benefit Data Lake Software Machine Learning 116

CDW Research Hub

JULY 27, 2021

Reduce the total cost of ownership of the data infrastructure. Build the foundation for a logical data warehouse or logical data lake. Maintain one consistent business data model across all consumers and reporting tools. Reuse analytical objects across multiple tools and consuming applications.

Data Warehouse 52

Data Warehouse Data Lake Data Architecture Consulting 52

Sisense

JULY 8, 2020

Traditionally, the extraction step of the process involves batch-pulling the data from the source via files, application database, or an API. In the transformation step , the data is cleaned and modeled so that it’s fit for analysis and ingestible by the data warehouse. The ETL process and data warehouses.

Data Warehouse 90

Data Warehouse Data Lake Data-driven Cost-Benefit 90

CIO Business Intelligence

JULY 12, 2023

P&G engineers developed a high-speed data collection system to capture data to use for training AI models. One challenge they faced is that, while production errors are extremely costly and disruptive, they don’t happen often, which means that failure events are underrepresented in the training data. says Cretella.

Manufacturing 91

Manufacturing Cost-Benefit Data Lake Optimization 91

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. This will be your online transaction processing (OLTP) data store for transactional data.

Data Analytics 91

Data Analytics Analytics Data Warehouse Data Lake 91

Cloudera

AUGUST 28, 2020

From a data perspective, once we have a huge increase in connected devices, there are also opportunities beyond connectivity and companies can diversify into IoT solutions, new platforms, and services. That requires real-time analytics and companies will have to have the capability to ingest and handle real-time streaming data. .

IoT 110

IoT Machine Learning B2B Testing 110

Sisense

JANUARY 8, 2021

For modern apps, that “something” is data and analytics. You have to deftly integrate data and analytics into your product to succeed. . Whatever your audience, your users are getting more and more used to seeing data and analytics infused throughout apps , products, and services of all kinds.

Cost-Benefit 98

Cost-Benefit Forecasting Data Lake Data-driven 98