CIO Business Intelligence

SEPTEMBER 14, 2023

Data engineers also need communication skills to work across departments and to understand what business leaders want to gain from the company’s large datasets. Data engineers must also know how to optimize data retrieval and how to develop dashboards, reports, and other visualizations for stakeholders.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 105

Data Lake Sales Data Warehouse Snapshot 105

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved.

Analytics 129

Analytics Data Science Statistics Unstructured Data 129

Sisense

MAY 28, 2020

As enterprises demand data infrastructures that can meet this growth in real-time data — and ultimately assist with their product differentiation strategy — the pressure put on product teams is huge. Product teams are already having to manage the growing complexities that come with modern data environments.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 57

Data Warehouse Unstructured Data Analytics Visualization 57

CIO Business Intelligence

AUGUST 18, 2022

The result is an emerging paradigm shift in how enterprises surface insights, one that sees them leaning on a new category of technology architected to help organizations maximize the value of their data. Enter the data lakehouse. You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

BizAcuity

APRIL 14, 2022

Netflix uses big data to make decisions on new productions, casting and marketing and generate millions in revenue through successful and strategic bets. Data Management. Before building a big data ecosystem, the goals of the organization and the data strategy should be very clear. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

CIO Business Intelligence

MAY 24, 2022

Australian research and advisory firm Adapt identifies an organisation’s ability to execute a data-driven strategy as one of 12 core competencies , identified from 30,000 conversations spanning three years with leading IT and businesses. This is the first post in a series of three on data-driven organisations.

Data-driven 90

Data-driven Data Lake Data Warehouse Cost-Benefit 90

Sisense

MAY 11, 2021

In this article, we’ll dig into what data modeling is, provide some best practices for setting up your data model, and walk through a handy way of thinking about data modeling that you can use when building your own. Building the right data model is an important part of your data strategy. Discover why.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

JULY 6, 2021

This cutting-edge service integrates the abilities of a data lake, a data warehouse, and purpose-built stores, to enable unified governance and easy data movement. The full range of Sisense features allows businesses to analyze all their data,” said Assaf Jacoby, Sisense AVP of Cloud Alliances.

Data Lake 52

Data Lake Data Warehouse Data-driven Unstructured Data 52

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Key steps include: Define business and data objectives –What are your company’s goals?

Data Architecture 62

Data Architecture Data Lake Machine Learning Data Governance 62