Octopai

FEBRUARY 20, 2022

Deciding to migrate your data from legacy, on-prem databases to a cloud-based data warehouse like Snowflake is often a step in the right direction. Develop a map of your ideal, streamlined, optimized data flow. Your spanking new modern data warehouse doesn’t need dirty, antiquated or otherwise irrelevant data.

Data Warehouse 92

Data Warehouse Optimization Measurement Visualization 92

Timo Elliott

JANUARY 3, 2022

It’s stored in corporate data warehouses, data lakes, and a myriad of other locations – and while some of it is put to good use, it’s estimated that around 73% of this data remains unexplored. Improving data quality. Unexamined and unused data is often of poor quality. Data augmentation.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

datapine

SEPTEMBER 27, 2022

Amongst the various topics that it covers, ”SQL Performance Explained” offers knowledge into: Correctly applying SQL functions Using indexes correctly How to use LIKE queries efficiently How to optimize join operations Data clustering Database scalability. The all-encompassing nature of this book makes it a must for a data bookshelf.

Business Intelligence 292

Business Intelligence Data Warehouse Data Processing Data mining 292

CIO Business Intelligence

MAY 23, 2024

More recently, products have become increasingly digital, with software that manages patient flows, tools for surgery planning, and sterile management processes that optimize inventory and ensure that surgical instruments are delivered at the right time to the right place.

Digital Transformation 111

Digital Transformation Measurement Cost-Benefit Data Warehouse 111

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Data lakes are more focused around storing and maintaining all the data in an organization in one place.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

CIO Business Intelligence

NOVEMBER 22, 2022

The next step in every organization’s data strategy, Guan says, should be investing in and leveraging artificial intelligence and machine learning to unlock more value out of their data. CIOs should first understand the different approaches to observing data and how it differs from quality management,” he notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

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 Digital Transformation 105

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Comprehensive search and access to relevant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

datapine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality? Who are they?

IT 317

IT Statistics KPI Data-driven 317

CIO Business Intelligence

AUGUST 9, 2022

What is a data engineer? Data engineers design, build, and optimize systems for data collection, storage, access, and analytics at scale. They create data pipelines used by data scientists, data-centric applications, and other data consumers. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

Timo Elliott

DECEMBER 14, 2022

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. You lose the roots: the metadata, the hierarchies, the security, the business context of the data. So how do organizations do that? Business Context.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

datapine

MAY 21, 2019

Armed with BI-based prowess, these organizations are a testament to the benefits of using online data analysis to enhance your organization’s processes and strategies. In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources.

Business Intelligence 183

Business Intelligence Cost-Benefit Dashboards ROI 183

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. They know how to assess data quality and understand data security, including row-level security and data sensitivity.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

AWS Big Data

JUNE 6, 2023

Data consumers lose trust in data if it isn’t accurate and recent, making data quality essential for undertaking optimal and correct decisions. Evaluation of the accuracy and freshness of data is a common task for engineers. Currently, various tools are available to evaluate data quality.

Data Quality 76

Data Quality Data Lake Data-driven Metrics 76

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 122

Cost-Benefit Internet of Things Data-driven Data Lake 122

Alation

SEPTEMBER 7, 2021

Now that you have empowered data scientists and analysts to access the Snowflake Data Cloud and speed their modeling and analysis, you need to bolster the effectiveness of your governance models. But governance is a time-consuming process (for users and data stewards alike). Find Trusted Data. Two problems arise.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 55

Analytics Data Lake Testing Optimization 55

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

MAY 16, 2019

The traditional Data Warehouse ETL process has splintered into many smaller components. Ingest is now focused data capture and real-time trend analysis where possible. Once data is brought under control in a system like Cloudera, then the work of Data Preparation, Quality begins.

Analytics 40

Analytics Data Warehouse Data-driven Data Integration 40

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 91

Optimization B2B Data Quality Sales 91

FineReport

MAY 31, 2023

Contemporary dashboards surpass basic visualization and reporting by utilizing financial analytics to amalgamate diverse financial and accounting data, empowering analysts to delve further into the data and uncover valuable insights that can optimize cost-efficiency and enhance profitability.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. For many organizations, however, the question remains, “Is it the right solution for us?”

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

CIO Business Intelligence

FEBRUARY 14, 2023

It’s clear how these real-time data sources generate data streams that need new data and ML models for accurate decisions. Data quality is crucial for real-time actions because decisions often can’t be taken back. An enterprise data ecosystem architected to optimize data flowing in both directions.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

AWS Big Data

FEBRUARY 1, 2023

This introduces the need for both polling and pushing the data to access and analyze in near-real time. From an operational standpoint, we designed a new shared responsibility model for data ingestion using AWS Glue instead of internal services (REST APIs) designed on Amazon EC2 to extract the data.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

DataKitchen

SEPTEMBER 21, 2023

In the contemporary data landscape, data teams commonly utilize data warehouses or lakes to arrange their data into L1, L2, and L3 layers. These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. What is Data in Use?

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

DataKitchen

APRIL 13, 2021

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

IBM Big Data Hub

DECEMBER 7, 2023

This siloed approach often resulted in data redundancy and complexity, hampering integration with other business systems. C-OLAP optimized data storage for faster query processing, while IM-OLAP stored data in memory to minimize data access latency and enable real-time analytics.

OLAP 57

OLAP Slice and Dice Cost-Benefit Data Warehouse 57

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

FEBRUARY 13, 2023

We live in a data-producing world, and as companies want to become data driven, there is the need to analyze more and more data. These analyses are often done using data warehouses. Status quo before migration Here at OLX Group, Amazon Redshift has been our choice for data warehouse for over 5 years.

Snapshot 68

Snapshot Data Warehouse Testing Analytics 68

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

CIO Business Intelligence

NOVEMBER 29, 2022

Layering technology on the overall data architecture introduces more complexity. Today, data architecture challenges and integration complexity impact the speed of innovation, data quality, data security, data governance, and just about anything important around generating value from data.

Data Architecture 111

Data Architecture Data Integration IoT Strategy 111

BI-Survey

FEBRUARY 17, 2020

With the growing interconnectedness of people, companies and devices, we are now accumulating increasing amounts of data from a growing variety of channels. New data (or combinations of data) enable innovative use cases and assist in optimizing internal processes. However, effectively using data needs to be learned.

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89