FineReport

MARCH 24, 2024

They analyze, interpret, and manipulate complex data, track key performance indicators, and present insights to management through reports and visualizations. Data analysts interpret data using statistical techniques, develop databases and data collection systems, and identify process improvement opportunities.

Statistics 52

Statistics Data mining Visualization Reporting 52

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. On the other hand, they don’t support transactions or enforce data quality.

Data Lake 101

Data Lake Unstructured Data Data Warehouse Data Quality 101

Data Virtualization

MARCH 7, 2024

Reading Time: 3 minutes As we move deeper into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies. One thing is clear; if data-centric organizations want to succeed in.

Management 59

Management Data Integration Strategy Data Lake 59

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

Data Virtualization

JANUARY 25, 2024

Reading Time: 3 minutes As we head into 2024, it is imperative for data management leaders to look in their rear-view mirrors to assess and, if needed, refine their data management strategies.

Management 59

Management Data Integration Strategy Data Lake 59

Alation

JULY 19, 2022

As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming. Obstacles, such as user roles, permissions, and approval request prevent speedy data access.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ).

Data Architecture 76

Data Architecture Data Lake Metadata Data Warehouse 76

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

Data Virtualization

MAY 19, 2023

Reading Time: 11 minutes The post Data Strategies for Getting Greater Business Value from Distributed Data appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Strategy 52

Data Strategy Strategy Data Integration Management 52

Cloudera

DECEMBER 15, 2022

With in-place table migration, you can rapidly convert to Iceberg tables since there is no need to regenerate data files. Newly generated metadata will then point to source data files as illustrated in the diagram below. . Data quality using table rollback. Only metadata will be regenerated.

Metadata 76

Metadata Data Warehouse Snapshot Data Quality 76

IBM Big Data Hub

APRIL 27, 2022

Since its uniquely metadata-driven, the abstraction layer of a data fabric makes it easier to model, integrate and query any data sources, build data pipelines, and integrate data in real-time. This improves data engineering productivity and time-to-value for data consumers. What’s a data mesh?

Management 87

Management Metadata Data Architecture Data Lake 87

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Quality is job one.

Unstructured Data 122

Unstructured Data Data-driven Visualization Data Quality 122

IBM Big Data Hub

DECEMBER 7, 2023

Automated data preparation and cleansing : AI-powered data preparation tools will automate data cleaning, transformation and normalization, reducing the time and effort required for manual data preparation and improving data quality.

OLAP 63

OLAP Slice and Dice Cost-Benefit Data Warehouse 63

TDAN

OCTOBER 1, 2019

Become a “Data-First” Company The organizations that invest in data first and foremost are changing the business landscape. Apple had famously reached a trillion dollar valuation on August 2, 2018, and analysts predicted that Amazon wasn’t far behind.

Management 68

Management Data Quality Data Lake IT 68

datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. His core area of expertise include Technology Strategy, Data Analytics, and Data Science.

Metadata 118

Metadata Visualization Data Lake Data-driven 118

Peter James Thomas

MAY 3, 2019

Leverage of Data to generate Insight. In this second area we have disciplines such as Analytics and Data Science. The objective here is to use a variety of techniques to tease out findings from available data (both internal and external) that go beyond the explicit purpose for which it was captured. Watch this space. [2].

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

Domino Data Lab

JUNE 15, 2021

These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. The typical data science journey for a company starts with a small team that is tasked with a handful of specific problems.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” According to Gartner, Inc.

Metadata 97

Metadata Machine Learning Unstructured Data Data Lake 97

Alation

SEPTEMBER 23, 2021

Guided Navigation – Guided navigation provides intelligent suggestions, which guide correct usage of data. Behavioral intelligence, embedded in the catalog, learns from user behavior to enforce best practices through features like data quality flags, which help folks stay compliant as they use data.

Enterprise 52

Enterprise Metadata Data Governance Visualization 52

Peter James Thomas

AUGUST 12, 2018

However, often the biggest stumbling block is a human one, getting people to buy in to the idea that the care and attention they pay to data capture will pay dividends later in the process. These and other areas are covered in greater detail in an older article, Using BI to drive improvements in data quality.

Metrics 49

Metrics Statistics Data Quality Measurement 49

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

Alation

AUGUST 4, 2022

And where data was available, the ability to access and interpret it proved problematic. Big data can grow too big fast. Left unchecked, data lakes became data swamps. Some data lake implementations required expensive ‘cleansing pumps’ to make them navigable again. Where Should Big Data Go from Here?

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Smarten

AUGUST 4, 2023

If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

AWS Big Data

NOVEMBER 16, 2023

One of the core features of AWS Lake Formation is the delegation of permissions on a subset of resources such as databases, tables, and columns in AWS Glue Data Catalog to data stewards, empowering them make decisions regarding who should get access to their resources and helping you decentralize the permissions management of your data lakes.

Management 110

Management Data Lake Sales Machine Learning 110

Alation

FEBRUARY 17, 2023

The firms that get data governance and management “right” bring people together and leverage a set of capabilities: (1) Agile; (2) Six sigma; (3) data science; and (4) project management tools. Some data seems more analytical, while other is operational (external facing). Establishing a solid vision and mission is key.

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Andrew White

JANUARY 11, 2021

As such a head of analytics, BI and data science may emerge. Are you anticipating continued separation of “BI/Analytics” teams from “Data Science” teams or are those roles merging in the years ahead? Many data science labs are set up as shared services. That’s the idea.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

Andrew White

MARCH 22, 2019

This ties into the failure of data governance and MDM (see first item in this list). A data hub strategy should be economical, not perfected; and a data hub does not collect data like a data warehouses or data lake does – they are very different things. Age maybe against us.

Analytics 68

Analytics Metadata Data Governance Management 68

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52