Smart Data Collective

FEBRUARY 20, 2022

During this process, you need to analyze your data assets, categorize and prioritize them, conduct a risk assessment, and establish appropriate monitoring and response techniques. DAM market trends and forecasts. A typical DAM deployment project can last from one month up to several years.

Behavioral Analytics 130

Behavioral Analytics Risk Machine Learning Interactive 130

Sisense

JUNE 8, 2020

Datasets are on the rise and most of that data is on the cloud. The recent rise of cloud data warehouses like Snowflake means businesses can better leverage all their data using Sisense seamlessly with products like the Snowflake Cloud Data Platform to strengthen their businesses. “The

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Jet Global

DECEMBER 8, 2020

A full Power BI implementation is a large-scale project, and it carries similar risks. If you are considering using Power BI in your organization, here are some key points to keep in mind that impact project risk: 1. Power BI Without the Risk. Power BI Is Highly Complex. That’s a relatively straightforward proposition.

Finance 52

Finance Risk Reporting Software 52

CIO Business Intelligence

SEPTEMBER 6, 2022

As a result, Pimblett now runs the organization’s data warehouse, analytics, and business intelligence. Establishing a clear and unified approach to data. Pimblett hasn’t yet catalogued all of Very’s data, however. We’re picking off the highest potential value and highest risk areas,” he says.

IT 98

IT Forecasting Data Lake Data Warehouse 98

Octopai

JANUARY 8, 2020

Octopai’s metadata discovery and management suite provides visualization tools that empower you to see and report everything about sensitive customer data. You can evaluate and mitigate compliance risks. On the Horizon: Federal Data Privacy Law. A vital component of business forecasting is automated metadata queries.

Metadata 72

Metadata Key Performance Indicator OLAP Forecasting 72

CIO Business Intelligence

SEPTEMBER 8, 2022

“The enormous potential of real-time data not only gives businesses agility, increased productivity, optimized decision-making, and valuable insights, but also provides beneficial forecasts, customer insights, potential risks, and opportunities,” said Krumova.

Cost-Benefit 122

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

IBM Big Data Hub

OCTOBER 30, 2023

Real-time data analytics helps in quick decision-making, while advanced forecasting algorithms predict product demand across diverse locations. AWS’s scalable infrastructure allows for rapid, large-scale implementation, ensuring agility and data security.

Insurance 77

Insurance Data Warehouse Data-driven Unstructured Data 77

AWS Big Data

MARCH 26, 2024

Enrichment typically involves adding demographic, behavioral, and geolocation data. You can use third-party data products from AWS Marketplace delivered through AWS Data Exchange to gain insights on income, consumption patterns, credit risk scores, and many more dimensions to further refine the customer experience.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

Cloudera

OCTOBER 30, 2017

As such, we’re seeing cloud-based big data growing exponentially for Cloudera customers and across the market as a whole. For these organizations, it’s essential that they are also managing the associated risks and costs of going to a cloud environment.

Big Data 40

Big Data Forecasting Optimization Marketing 40

Jet Global

JANUARY 15, 2021

You might measure those costs in different ways, including actual dollars and cents, staff time, added complexity, and risk. There are numerous soft costs involving risk and potential business disruption. A non-developer can build a custom data warehouse with Jet Analytics in as little as 30 minutes.

Cost-Benefit 72

Cost-Benefit Data Lake Reporting OLAP 72

CIO Business Intelligence

OCTOBER 10, 2022

The company also wanted to improve forecasting accuracy by harnessing the power of intelligent technologies. Achieve 10x faster-planning cycles despite having larger data volumes . FHCS integrated its landscape built on SAP ERP and SAP Business Warehouse with specialized forecasting in SAP Integrated Business Planning (IBP).

Enterprise 52

Enterprise Forecasting Descriptive Analytics Data Warehouse 52

AWS Big Data

OCTOBER 26, 2023

Amazon Redshift is a fast, petabyte-scale, cloud data warehouse that tens of thousands of customers rely on to power their analytics workloads. To get started, we need an Amazon Redshift Serverless data warehouse with the Redshift ML feature enabled and an Amazon SageMaker Studio environment with access to SageMaker Feature Store.

Modeling 69

Modeling Data Warehouse Machine Learning Testing 69

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 57

OLAP Slice and Dice Cost-Benefit Data Warehouse 57

Sisense

FEBRUARY 24, 2021

Whether that data is generated internally or gathered from an external application used by customers, organizations now use on-demand cloud computing resources to make sense of the data, discover trends, and make intelligent forecasts. This is one approach to solving the challenge of data silos.

Data Warehouse 69

Data Warehouse Big Data Metrics Visualization 69

IBM Big Data Hub

MAY 17, 2023

They use drones for tasks as simple as aerial photography or as complex as sophisticated data collection and processing. billion by 2029, at a CAGR of 28.58% in the forecast period. Knowledge catalogues can help organize data effectively, and the data refinery provides out-of-box models for data cleansing.

Data Collection 76

Data Collection Visualization Data-driven Unstructured Data 76

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake. Learn more about IBM watsonx 1.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Modeling 76

IBM Big Data Hub

JULY 6, 2023

Data from various sources, collected in different forms, require data entry and compilation. That can be made easier today with virtual data warehouses that have a centralized platform where data from different sources can be stored. One challenge in applying data science is to identify pertinent business issues.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

Sisense

APRIL 22, 2021

She quickly noticed that employees couldn’t access data quickly enough to be proactive in decision-making. Managers couldn’t decide which sites to visit first and what risks were involved. Paula decided that data and analytics would help TCFM improve efficiencies in the business. The second factor was customers.

Management 52

Management Dashboards Analytics Cost-Benefit 52

Alation

APRIL 6, 2023

Spreadsheets are not typically developed and managed for enterprise use, which opens the door to risk from malicious actors, as well as human errors. A “Value at Risk” (VaR) model operated on a series of spreadsheets, which were built manually, via copy and paste. Leaders seek to use strategic data with confidence more often.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

BizAcuity

APRIL 14, 2022

Be it supply chain resilience, staff management, trend identification, budget planning, risk and fraud management, big data increases efficiency by making data-driven predictions and forecasts. With adequate market intelligence, big data analytics can be used for unearthing scope for product improvement or innovation.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

IBM Big Data Hub

OCTOBER 16, 2023

ML also helps businesses forecast and decrease customer churn (the rate at which a company loses customers), a widespread use of big data. AI and ML use decades of stock market data to forecast trends and suggest whether to buy or sell. ML can also conduct algorithmic trading without human intervention.

Machine Learning 48

Machine Learning Marketing Forecasting Modeling 48

Cloudera

MARCH 2, 2018

The private sector already very successfully uses data analytics and machine learning not only to realise efficiency gains but also – even more importantly – to create completely new services and business models. Identify those most at risk or most affected by a problem more accurately by using predictive analytics.

Data-driven 43

Data-driven Prescriptive Analytics Machine Learning Descriptive Analytics 43

Smarten

NOVEMBER 22, 2017

Fortunately, today’s new self-serve business intelligence solutions allow for ease-of-use, bringing together these varied techniques in a simple interface with tools that allow business users to utilize advanced analytics without the skill or knowledge of a data scientist, analyst or IT team member.

Analytics 40

Analytics IT Business Intelligence Visualization 40

Domino Data Lab

FEBRUARY 4, 2019

Eric’s article describes an approach to process for data science teams in a stark contrast to the risk management practices of Agile process, such as timeboxing. As the article explains, data science is set apart from other business functions by two fundamental aspects: Relatively low costs for exploration.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

FineReport

MAY 31, 2023

Budget variance quantifies the discrepancy between budgeted and actual figures, enabling forecasters to make more accurate predictions regarding future costs and revenues. Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

datapine

AUGUST 29, 2022

The book has three main ideas: The biggest risk your company faces is investing a lot of time and resources into building something that the market doesn’t want. and this book will give you an insight into their data collecting procedures and the reasons behind them. Product/market fit is THE most important factor to get right.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

DataRobot

JANUARY 20, 2022

The UK’s National Health Service (NHS) will be legally organized into Integrated Care Systems from April 1, 2022, and this convergence sets a mandate for an acceleration of data integration, intelligence creation, and forecasting across regions. Public sector data sharing.

Data-driven 145

Data-driven Experimentation Predictive Modeling Data Warehouse 145

Andrew White

JANUARY 11, 2021

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Risk Management (most likely within context of governance).

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

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. Facilitates a Data-Driven Culture that Enables Collaboration.

Data Governance 52

Data Governance Analytics Cost-Benefit Data-driven 52

Jet Global

MAY 1, 2023

Healthcare is forecasted for significant growth in the near future. CFO Priorities Manage expenses and cash flow Enable profitable growth Contain risk Plan for the future Connect the Dots Do the math. These sit on top of data warehouses that are strictly governed by IT departments. Present your business case.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

JUNE 17, 2024

Cash flow projections (also known as cash flow forecasting ) is the process of estimating and predicting the cash inflows, cash outflows, and cash balance a business can expect over a specific period of time, typically in the short- to medium-term.

Forecasting 52

Forecasting Finance Sales Cost-Benefit 52

Jet Global

APRIL 5, 2021

Executives typically use financial models to make decisions regarding: Budgeting and forecasting. Risk management. That means the FP&As are the people creating the budget and performing financial forecasting to help the CFO and other members of senior management understand the company’s financial situation.

Modeling 98

Modeling Forecasting Metrics Finance 98

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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

Jet Global

SEPTEMBER 1, 2023

But we’re also seeing its use expand in other industries, like Financial Services applications for credit risk assessment or Human Resources applications to identify employee trends. Analysts can use predictive analytics to foresee if a change will help them reduce risks, improve operations, and/or increase revenue.

Predictive Analytics 52

Predictive Analytics Risk Analytics Software 52

Jet Global

JUNE 17, 2021

Although the workbooks were standardized, data entered were not always complete or in line with numbers forecast earlier in the year. The semi-manual approach to data capture also led to inaccuracies that needed to be managed and corrected centrally. The Need to Free Up Time. User Acceptance.

Risk 98

Risk Recreation/Entertainment Forecasting Manufacturing 98

Jet Global

NOVEMBER 16, 2022

Accuracy of Forecast Demand. Forecasting is a crucial part of reporting. The accuracy of the forecast metric gives you an idea of how confident you can be in your projections of how well a particular item will sell. Accuracy of forecast demand = [(actual demand – forecast demand) / actual demand] X 100.

Metrics 52

Metrics Reporting KPI Cost-Benefit 52

Jet Global

JANUARY 31, 2022

In most companies, planning, budgeting, and forecasting processes are fairly well-established, but just because you’ve always done things a certain way doesn’t mean you can’t improve them. Monitor, Forecast, and Adjust. The idea of changing your approach to planning, budgeting, and forecasting may seem daunting.

Forecasting 52

Forecasting Recreation/Entertainment Finance Cost-Benefit 52