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

Boris Evelson

JUNE 14, 2023

No matter what technology foundation you’re using – a data lake, a data warehouse, data fabric, data mesh, etc. – BI applications are where business users consume data and turn it into actionable insights and decisions. The BI market has […]

Business Intelligence 98

Business Intelligence Data Lake Data Warehouse Data-driven 98

AWS Big Data

NOVEMBER 8, 2023

Proposed Solution approach 2: Data Lake analytics The team used this approach with Redshift Spectrum to load only the required columns to Redshift Serverless, which avoided loading data into multiple yearly tables and directly to a single table. Create a data lake external schema and table in Redshift Serverless.

Data Lake 94

Data Lake Data Warehouse Cost-Benefit Optimization 94

CIO Business Intelligence

DECEMBER 1, 2022

The $247 billion conglomerate, one of the largest food and beverage companies in the world, is developing a modernized data and cloud infrastructure replete with automated processes and workflows.

Digital Transformation 144

Digital Transformation IoT Data-driven KPI 144

CIO Business Intelligence

JUNE 20, 2024

These cover the many processes involved, from data discovery to the creation of data lakes, predictive analytics, and guidance for new use cases and applications. Notably, TIVIT also fields teams that specialize in AI and machine learning.

Digital Transformation 98

Digital Transformation Data Lake Predictive Analytics Machine Learning 98

CIO Business Intelligence

APRIL 26, 2022

Backcountry also lacked many core services critical for an online retailer — no CMS, no analytics, no data platform, and no data lake. In recent years, e-commerce platforms have evolved into a combination of cloud, analytics, CX UIs, and data lakes dubbed customer data platforms (CDPs).

Data Lake 98

Data Lake Dashboards Recreation/Entertainment Sales 98

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Cloudera

AUGUST 18, 2021

Data processed at the edge or in the cloud, for instance, is not effective if it follows the traditional lifecycle of “ingest, process, land, and analyze.” If the data goes into a data lake before analysis, extracting it can get pretty complex and time-consuming.

Data Lake 88

Data Lake IoT Internet of Things Data-driven 88

Smart Data Collective

MARCH 21, 2022

Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. Even today, there are a large number of them using data lakes to drive predictive analytics. The cloud age did address that issue to a certain extent.

Management 75

Management Data Lake Uncertainty Data Warehouse 75

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

CIO Business Intelligence

MAY 21, 2024

Real-Time Intelligence, on the other hand, takes that further by supporting data in AWS, Google Cloud Platform, Kafka installations, and on-prem installations. “We We introduced the Real-Time Hub,” says Arun Ulagaratchagan, CVP, Azure Data at Microsoft. You can monitor and act on the data and you can set thresholds.”

Broadcasting 126

Broadcasting Recreation/Entertainment Manufacturing Data Lake 126

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

Sisense

JUNE 30, 2020

Prescriptive analytics takes things a stage further: In addition to helping organizations understand causes, it helps them learn from what’s happened and shape tactics and strategies that can improve their current performance and their profitability. Predictive analytics is the most beneficial, but arguably the most complex type.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

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. To get started with this feature, see Querying the AWS Glue Data Catalog. Satesh Sonti is a Sr.

Data Analytics 113

Data Analytics Analytics Data Warehouse Data Lake 113

Cloudera

SEPTEMBER 12, 2022

Companies need answers to more complex business questions that require integration of unstructured data, real time data with use of modern, best-of-breed engines for analytics, stream processing, and for AI and ML for predictive analytics. These answers must be reliable and delivered quickly.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

CIO Business Intelligence

APRIL 14, 2022

ATD also uses UiPath robotic process automation to automate various business processes, and it relies on SAP Hybris commerce on premise, Power BI for data visualization, and Snowflake for its data lake.

B2B 98

B2B Digital Transformation Data Lake Sales 98

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos.

Data Lake 46

Data Lake Finance Data Governance Big Data 46

Corinium

APRIL 25, 2019

I’ve found many IT as well as Business leaders have a mental model of data in that it is simply part of, or belongs to, a specific database or application, and thus they falsely conclude that just procuring a tool to protect that given environment will sufficiently protect that data. In data-driven organizations, data is flowing.

Insurance 150

Insurance Risk IoT Data-driven 150

IBM Big Data Hub

SEPTEMBER 19, 2023

Having the right data strategy and data architecture is especially important for an organization that plans to use automation and AI for its data analytics. The types of data analytics Predictive analytics: Predictive analytics helps to identify trends, correlations and causation within one or more datasets.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Jedox

OCTOBER 22, 2020

In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

In(tegrate) the Clouds

AUGUST 4, 2016

Also driving this trend is the fact that cloud data warehousing and analytics have moved from rogue departmental use cases to enterprise deployments. It’s already happening today in some industries with data velocity, variety, and, of course, volume. The third trend is the Internet of Things (IoT).

IoT 45

IoT Internet of Things Data Lake Data Warehouse 45

Sisense

OCTOBER 6, 2020

Traditional methods of gathering and organizing data can’t organize, filter, and analyze this kind of data effectively. What seem at first to be very random, disparate forms of qualitative data require the capacity of data warehouses , data lakes , and NoSQL databases to store and manage them.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. Let’s find out what role each of these components play in the context of C360.

Data Strategy 84

Data Strategy Strategy Data Warehouse Prescriptive Analytics 84

BizAcuity

MAY 16, 2022

Whereas, integrating data sources can provide you with a picture of where your customer is coming from, how long they spend on your website, what can be improved in the entire buying process among others. Integrating data allows you to perform cross-database queries, which like portals provide you with endless possibilities.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

Cloudera

JANUARY 22, 2019

Forrester describes Big Data Fabric as, “A unified, trusted, and comprehensive view of business data produced by orchestrating data sources automatically, intelligently, and securely, then preparing and processing them in big data platforms such as Hadoop and Apache Spark, data lakes, in-memory, and NoSQL.”.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

IBM Big Data Hub

DECEMBER 7, 2023

Here’s an overview of the key characteristics: AI-powered analytics : Integration of AI and machine learning capabilities into OLAP engines will enable real-time insights, predictive analytics and anomaly detection, providing businesses with actionable insights to drive informed decisions.

OLAP 57

OLAP Slice and Dice Cost-Benefit Data Warehouse 57

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

DataKitchen

DECEMBER 9, 2022

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

IBM Big Data Hub

JULY 17, 2023

Watsonx.data is built on 3 core integrated components: multiple query engines, a catalog that keeps track of metadata, and storage and relational data sources which the query engines directly access.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Alation

MARCH 21, 2023

Seasonality and trend predictions Many online travel companies use dynamic and flexible pricing strategies to respond to changes in demand and supply. Using predictive analytics, travel companies can forecast customer demand around things like holidays or weather to set optimum prices that maximize revenue.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

AWS Big Data

JULY 12, 2023

It automatically provisions and scales the data warehouse capacity to deliver high performance for demanding and unpredictable workloads, and you only pay for the resources you use. Amazon Redshift delivers up to five times better price performance than other cloud data warehouses out of the box and helps you keep costs predictable.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

FineReport

MARCH 24, 2024

Diagnostic analytics: Uncovering the reasons behind specific occurrences through pattern analysis. Descriptive analytics: Assessing historical trends, such as sales and revenue. Predictive analytics: Forecasting likely outcomes based on patterns and trends to facilitate proactive decision-making.

Statistics 52

Statistics Data mining Visualization Reporting 52

Data Virtualization

MAY 13, 2022

Reading Time: 3 minutes Join our conversation on All Things Data with Robin Tandon, Director of Product Marketing at Denodo (EMEA & LATAM), with a focus on how data virtualization helps customers realize true economic benefits in as little as six weeks.

Data Integration 52

Data Integration Marketing Management Data Warehouse 52

Data Virtualization

SEPTEMBER 23, 2020

Denodo is a very partner-friendly company, and here I’d like to share some thoughts about how Denodo works with our partners. I’m referring not only to our technology partners, but also to our cloud partners that host the Denodo Platform,

Strategy 52

Strategy Data Processing Technology Digital Transformation 52

datapine

AUGUST 29, 2022

The new edition also explores artificial intelligence in more detail, covering topics such as Data Lakes and Data Sharing practices. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz. An excerpt from a rave review: “The Freakonomics of big data.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

MAY 16, 2024

About Amazon Redshift Thousands of customers rely on Amazon Redshift to analyze data from terabytes to petabytes and run complex analytical queries. With Amazon Redshift, you can get real-time insights and predictive analytics on all of your data across your operational databases, data lake, data warehouse, and third-party datasets.

Data Warehouse 119

Data Warehouse Visualization Cost-Benefit Data-driven 119

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift empowers users to extract powerful insights by securely and cost-effectively analyzing data across data warehouses, operational databases, data lakes, third-party data stores, and streaming sources using zero-ETL approaches.

Data Warehouse 111

Data Warehouse Machine Learning Data-driven Data Lake 111