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 127

Data Architecture Data Warehouse Statistics Visualization 127

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 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

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 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

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

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. The cloud age did address that issue to a certain extent.

Management 67

Management Data Lake Uncertainty Data Warehouse 67

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 97

Data Lake Dashboards Recreation/Entertainment Sales 97

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

CIO Business Intelligence

DECEMBER 1, 2022

Now halfway into its five-year digital transformation, PepsiCo has checked off many important boxes — including employee buy-in, Kanioura says, “because one way or another every associate in every plant, data center, data warehouse, and store are using a derivative of this transformation.”

Digital Transformation 125

Digital Transformation IoT Data-driven KPI 125

AWS Big Data

JULY 12, 2023

Introduction to Amazon Redshift Amazon Redshift is a fast, fully-managed, self-learning, self-tuning, petabyte-scale, ANSI-SQL compatible, and secure cloud data warehouse. Thousands of customers use Amazon Redshift to analyze exabytes of data and run complex analytical queries.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

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. Cloudera has supported data lakehouses for over five years.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

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

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

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

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

AWS Big Data

APRIL 28, 2023

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. You can unload data in either text or Parquet format.

Interactive 91

Interactive Metadata Data Warehouse Data-driven 91

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

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 Cost-Benefit 150

CIO Business Intelligence

AUGUST 18, 2022

Previously, Walgreens was attempting to perform that task with its data lake but faced two significant obstacles: cost and time. Those challenges are well-known to many organizations as they have sought to obtain analytical knowledge from their vast amounts of data. Lakehouses redeem the failures of some data lakes.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

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

IBM Big Data Hub

DECEMBER 7, 2023

Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses. They are seamlessly integrated with cloud-based data warehouses, facilitating the collection, storage and analysis of data from various sources.

OLAP 58

OLAP Slice and Dice Cost-Benefit Data Warehouse 58

Andrew White

JANUARY 11, 2021

Data and Analytics Governance: Whats Broken, and What We Need To Do To Fix It. Link Data to Business Outcomes. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? Data lakes don’t offer this nor should they. Policy enforcement.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

IBM Big Data Hub

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

AWS Big Data

DECEMBER 18, 2023

Amazon Redshift powers data-driven decisions for tens of thousands of customers every day with a fully managed, AI-powered cloud data warehouse, delivering the best price-performance for your analytics workloads.

Data Warehouse 99

Data Warehouse Machine Learning Data-driven Data Lake 99

CIO Business Intelligence

AUGUST 3, 2023

It also used device data to develop Lenovo Device Intelligence, which uses AI-driven predictive analytics to help customers understand and proactively prevent and solve potential IT issues. Each of the acquired companies had multiple data sets with different primary keys, says Hepworth. “We

Analytics 89

Analytics Data Lake Metadata Cost-Benefit 89

Alation

JANUARY 27, 2022

Raw data includes market research, sales data, customer transactions, and more. Analytics can identify patterns that depict risks, opportunities, and trends. And historical data can be used to inform predictive analytic models, which forecast the future. What Is the Value of Analytics?

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52