CIO Business Intelligence

SEPTEMBER 22, 2023

Data management platform definition A data management platform (DMP) is a suite of tools that helps organizations to collect and manage data from a wide array of first-, second-, and third-party sources and to create reports and build customer profiles as part of targeted personalization campaigns.

Management 101

Management Advertising Data Lake Sales 101

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption. This is the Data Mart stage.

Data Lake 91

Data Lake Data Warehouse Data-driven B2B 91

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

CIO Business Intelligence

MAY 24, 2022

Deloitte lists these as: Creating and shaping a common data foundation. Defining and using single data points for multiple purposes. Building a semantic layer describing unified business and reporting definitions. store and process the data, typically in a data warehouse, where the data is modelled and schema applied.

Data-driven 82

Data-driven Data Lake Data Warehouse Cost-Benefit 82

CIO Business Intelligence

MAY 10, 2023

Yet if we come across an ERP that’s not necessarily mainstream, they’ll have challenges getting into the back end, and integrating and understanding the relational data to connect it to our central data lake. Business Intelligence, CIO, Digital Transformation, Enterprise Architecture, IT Leadership

Data-driven 97

Data-driven IT Digital Transformation Data Governance 97

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. When can you declare it done?

Testing 152

Testing Metadata Dashboards Statistics 152

CIO Business Intelligence

OCTOBER 25, 2022

The variables seem endless: data— security , science , storage , mining , management , definition , deletion , integration , accessibility , architecture , collection , governance , and the ever-elusive, data culture. So, they built a data-lake. The data lake, too, took on new purpose.

Data Strategy 140

Data Strategy Strategy Data Lake Data-driven 140

datapine

AUGUST 29, 2022

Companies, both big and small, are seeking the finest ways to leverage their data into a competitive advantage. With that in mind, we have prepared a list of the top 19 definitive data analytics and big data books, along with magazines and authentic readers’ reviews upvoted by the Goodreads community. trillion each year.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog. Outside of work she enjoys traveling and trying new cuisines.

Measurement 85

Measurement Dashboards Data Warehouse Analytics 85

Paul Blogs on BI

SEPTEMBER 8, 2021

While we have definitely seen an acceleration in organizations using or moving operational applications to the cloud, Business Intelligence has lagged behind. Today, the majority of BusinessObjects customers use the product on premise and that will not change for a while.

Data Warehouse 59

Data Warehouse Data Processing Data Lake Testing 59

Cloudera

JANUARY 21, 2021

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. The Data Lake service in Cloudera’s Data Platform provides a central place to understand, manage, secure, and govern data assets across the enterprise.

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

CIO Business Intelligence

FEBRUARY 10, 2023

While managing unstructured data remains a challenge for 36% of organizations, according to the 2022 Foundry Data and Analytics Research survey, many IT leaders are actively seeking ways of harnessing all types of data stored in data lakes. But this is a superficial definition of multicloud, Randich says.

Unstructured Data 104

Unstructured Data Data Lake Machine Learning Enterprise 104

AWS Big Data

JULY 13, 2023

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. The AWS Glue crawler populates the table definition with its schema in AWS Glue Data Catalog.

Optimization 92

Optimization B2B Data Quality Sales 92

Jen Stirrup

MARCH 9, 2019

I tried to connect my Azure Data Lake gen 2 storage to Power BI, and I ran into this error message: ”Your Azure storage account must be in the same Azure Active Directory tenant as your Power BI tenant.’ ’ I checked, and my Azure storage account was definitely in the same Azure Active Directory tenant as Power BI. .’

Data Lake 49

Data Lake IT Business Intelligence 49

AWS Big Data

AUGUST 31, 2023

Data warehousing provides a business with several benefits such as advanced business intelligence and data consistency. Amazon Redshift is a fast, fully managed, cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data.

Data Warehouse 85

Data Warehouse Data-driven Testing Business Intelligence 85

CIO Business Intelligence

JUNE 6, 2023

“The same should apply to the data that people in organizations need.” However, most enterprises treat data as a centralized and protected asset. It’s locked up in production applications, data warehouses, and data lakes that are administered by a small cadre of technical specialists.

Management 52

Management Data Warehouse Data Lake Digital Transformation 52

Sisense

DECEMBER 11, 2019

With Itzik’s wisdom fresh in everyone’s minds, Scott Castle, Sisense General Manager, Data Business, shared his view on the role of modern data teams. Scott whisked us through the history of business intelligence from its first definition in 1958 to the current rise of Big Data.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

AWS Big Data

MARCH 27, 2023

To visualize data stored in Confluent, you can use one of over 120 pre-built connectors, provided by Confluent, to write streaming data to a destination data store of your choice. Next, you connect your business intelligence (BI) tool to the data store to begin visualizing the data.

Visualization 78

Visualization Data Lake Interactive Data-driven 78

CIO Business Intelligence

MARCH 14, 2024

In his business continuity project, Deligia’s team of about 20 internal resources and the outsourced IT team is responsible for merging technical data, such as digital service operation logs, and business and sales data into a data lake.

Digital Transformation 85

Digital Transformation Sales Forecasting Data Lake 85

BizAcuity

MAY 10, 2022

Companies planning to scale their business in the next few years without a definite cloud strategy might want to reconsider. Microsoft also releases Power BI, a data visualization and business intelligence tool. Data management solutions will need to keep up with the data demands of the next few years.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Cloudera

FEBRUARY 8, 2024

Apache Iceberg forms the core foundation for Cloudera’s Open Data Lakehouse with the Cloudera Data Platform (CDP). Materialized views are valuable for accelerating common classes of business intelligence (BI) queries that consist of joins, group-bys and aggregate functions.

Snapshot 90

Snapshot Metadata Cost-Benefit Data Warehouse 90

Birst BI

JANUARY 23, 2018

Data semantics are everything. Many IT and data management professionals posit that a single central data repository, such as a large cloud data warehouse or a data lake, is the definitive “single version of the truth.” For example, the definition of “profit” can be quite complex.

Data Warehouse 50

Data Warehouse Data Governance Data Lake Enterprise 50

CIO Business Intelligence

OCTOBER 19, 2022

“So, at Zebra, we created a hub-and-spoke model, where the hub is data engineering and the spokes are machine learning experts embedded in the business functions. We kept the data warehouse but augmented it with a cloud-based enterprise data lake and ML platform. The CIO of the future So, there you have it!

IT 115

IT Digital Transformation Data Warehouse Risk 115

AWS Big Data

FEBRUARY 21, 2023

Any change to the dimension definition results in a lengthy and time-consuming reprocessing of the dimension data, which often results in data redundancy. Another issue is that, when relying merely on dimensional modeling, analysts can’t assure the consistency and accuracy of data sources. What is a data vault?

Data Warehouse 67

Data Warehouse Data Lake Cost-Benefit Modeling 67

CIO Business Intelligence

APRIL 22, 2024

Per esempio, “i PoC aiutano a definire i parametri in base ai quali organizzare i data lake o i criteri per la digitalizzazione dei workflow. Esposito inizia conducendo dei Proof-of-Concept (PoC) o pilota, perché – spiega – nei progetti più strutturati aiutano nella standardizzazione.

Data Lake 94

Data Lake Testing Management IoT 94

AWS Big Data

JULY 25, 2023

It automatically provisions and intelligently scales data warehouse compute capacity to deliver fast performance, and you pay only for what you use. Just load your data and start querying right away in the Amazon Redshift Query Editor or in your favorite business intelligence (BI) tool.

Metrics 83

Metrics Data Warehouse Dashboards Snapshot 83

CIO Business Intelligence

MAY 26, 2022

It definitely still needs a lot of work because it’s such a new field.”. Companies don’t need to move all the data to a single platform, but there does need to be a way to bring in data from disparate data sources, she says, and this can vary based on application.

Machine Learning 141

Machine Learning Modeling Data-driven Dashboards 141

Octopai

MAY 30, 2019

If the point of Business Intelligence (BI) data governance is to leverage your datasets to support information transparency and decision-making, then it’s fair to say that the data catalog is key for your BI strategy. At least, as far as data analysis is concerned. The Benefits of Structured Data Catalogs.

Metadata 40

Metadata Data Governance Data Lake IoT 40

CIO Business Intelligence

MAY 28, 2022

It definitely still needs a lot of work because it’s such a new field.”. Companies don’t need to move all the data to a single platform, but there does need to be a way to bring in data from disparate data sources, she says, and this can vary based on application.

Machine Learning 129

Machine Learning Modeling Data-driven Dashboards 129

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Alation

JANUARY 26, 2023

Lack of data governance can summon a whole range of problems, including: Lack of consistency For data to be useful, it should be consistent across all areas. A field might not be entered in the same way across different departments, which makes the data difficult to find and affects the accuracy of business intelligence (BI).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Cloudera

OCTOBER 26, 2017

Become more agile with business intelligence and data analytics. Friction associated with getting a data sandbox has also resulted in the proliferation of spreadmarts , unmanaged data marts, or other data extracts used for siloed data analysis. Published originally on O’Reilly.com.

Cost-Benefit 43

Cost-Benefit Business Intelligence Data Warehouse Data Lake 43

Alation

APRIL 14, 2022

For example, data science always consumes “historical” data, and there is no guarantee that the semantics of older datasets are the same, even if their names are unchanged. Pushing data to a data lake and assuming it is ready for use is shortsighted. On-premises business intelligence and databases.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Birst BI

OCTOBER 24, 2019

What is your definition of DaaS? DaaS is a core component of modern data architecture. It provides a governed standard for accessing existing data objects and pipelines for sharing new data objects within an organization. This includes ETL processes and subsequent augmented and extended data sets.

Data Warehouse 51

Data Warehouse Recreation/Entertainment Data Lake Data Architecture 51

Domino Data Lab

APRIL 3, 2019

Look toward the evolving changes in system architecture to understand where data governance will be heading. Definition and Descriptions. We’ll start with standard definitions – the currently accepted wisdom in the industry. That definition plus the one-liner provide good starting points. In other words, #adulting.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Domino Data Lab

JUNE 15, 2021

At a certain point, as the demand keeps growing, the data volumes rapidly increase. Data is no longer stored in CSV files, but in a dedicated, purpose built data lake / data warehouse. This definition makes UDFs somewhat similar to stored procedures, but there are a number of key differences between the two.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69