Wipro’s Demand Forecasting of Critical Wellhead Spares app uses historical sales transactions data for the different product lines as well as publicly available data on crude oil prices and rig counts. The app built on Wipro’s Data Discovery Platform (DDP) helps supply chain managers to develop accurate demand forecasts to use as input into their procurement, manufacturing, and inventory planning process. DDP is an integrated platform that captures and manages data to generate pertinent insights through advanced analytics, offering price, performance and time benefits. It accelerates ‘time-to-insight’ for an enterprise using pre-built industry apps that enable faster decision making, aided by advanced visualization. Wipro’s Demand Forecasting of Critical Wellhead Spares app uses historical sales transactions data for the different product lines as well as publicly available data on crude oil prices and rig counts. The app built on Wipro’s Data Discovery Platform (DDP) helps supply chain managers to develop accurate demand forecasts to use as input into their procurement, manufacturing, and inventory planning process. This app can be applied across industries to forecast demand for product sales as well as to forecast demand for spare parts used to repair and refurbish the installed base. • Wipro’s Demand Forecasting App is designed to help a manufacturer accurately forecast the demand for spare parts for oil & gas wells in various regions. ABC analysis is performed and C category items are eliminated from the model because the dollar value for their sales made them a low financial risk. The model is therefore focused on critical wellhead spares. The Demand Forecasting App uses statistical models (time series models) for forecasting the demand based on historical unit sales. It also accounts for external factors such as crude oil prices and number of oil rigs in production to qualify as control variables, based on which the forecast becomes more appropriate and precise. The model is validated against a 3 month hold out sample and forecast accuracy ranging from 83% to 93% is achieved depending on the product group
Data, if leveraged wisely, can help you unlock insights that can assist you in making informed business decisions.
Let’s look at the different processes involved in the overall data lifecycle, right from the collection and preparation to processing and interpretation.Data IngestionIngesting data from diverse sources to a single storage medium where it may be accessed, used, and analyzed by an organization is known as data ingestion.
You can ingest data from complex sources like SAP Business API services (BAPI), Double Click Manager (DCM), etc.
DataBlaze Software, a Data Integration tool offers significant value to its users through its key features including knowledge graph, automated metadata mapper, machine learning pipeline, augmented data discovery, strategy processor, and dataset for visualization.Data AugmentationData augmentation refers to strategies for increasing the quantity of data by adding slightly changed copies of current data or creating new synthetic data from existing data.
AutoML and Google AutoAugment can also be used for determining which augmentations will work best for the dataset at hand.
Data DiscoveryData discovery is the process of gathering and analyzing data from multiple sources to identify trends and patterns in the data.
The global sensitive data discovery market size to grow from USD 5.1 billion in 2020 to USD 12.4 billion by 2026, at a Compound Annual Growth Rate (CAGR) of 16.1% during the forecast period.
Various factors such as the growing need to discover sensitive structured and unstructured data, increasing investments in data privacy with evolving regulations, and rise in remote workers and real-time data access are expected to drive the adoption of the sensitive data discovery solutions and services.Sensitive data discovery is the process of identifying and locating sensitive data to protect or securely remove pieces compromising information.
Sensitive data discovery solutions remediate compliance breaches in real-time and quarantine, delete, or revoke access to exposed data.Download PDF Brochure @ https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=191231584Some of the key players operating in the sensitive data discovery market include IBM (US),Microsoft (US),Oracle (US), AWS (US), Proofpoint (US), Google (US), SolarWinds (US), Micro Focus (UK), PKWARE (US), Thales (France), Spirion (US), Egnyte (US), Netwrix (US), Varonis (US), Digital Guardian (US), Solix (US), Immuta (US), MENTIS (US), Ground Labs (US), Hitachi (Japan), Nightfall (US), Securiti (US), DataGrail (US), Dathena (Singapore), BigID (US), DataSunrise (US), and 1touch.io (US).
These sensitive data discovery vendors have adopted various organic and inorganic strategies to sustain their positions and increase their market shares in the global sensitive data discovery market.IBM was founded in 1911 and is headquartered in New York, US.
As of December 31, 2019, IBM’s total employee strength, including that of its wholly owned subsidiaries, was 352,600.
IBM offers smarter data protection platform that offers actionable insights, real-time controls, and automated compliance support through data discovery and classification.
Report Scenario:Market Research Future (MRFR) announces the publication of its half-cooked research report—Global Data Discovery Market, 2020–2026.According to Market Research Future, the global Data Discovery Market has been segmented based on component, deployment, organization size, functionality, application, and region/country.Data discovery is the methodology of gaining meaningful business insights by collecting and evaluating raw from various data sources.
This usually is used to identify the trends and patterns in an organization.
The data discovery applications include security & risk management, sales & marketing management, asset management, supply chain management, and others.Request a Free Sample @ https://www.marketresearchfuture.com/sample_request/10513Competitive Outlook:The key players in the global data discovery market are IBM Corporation (US), Microsoft (US), Oracle (US), Salesforce.com, inc. (US), SAS Institute Inc. (US), Google (US), Amazon Web Services, Inc. (US), Micro Focus (UK), Thales (US), Cloudera, Inc. (US), Alteryx, Inc. (US), PKWARE, Inc. (US), Spirion, LLC.
(US), Egnyte, Inc. (US), and Netwrix Corporation (US).Segmentation:By component, the global data discovery market has been divided into solution and services.
Additionally, the services segment comprises professional and managed services.Based on the deployment, the global data discovery market is categorized into on-premises and on-cloud.By organization size, the global data discovery market has been divided into small & medium enterprise and large enterprise.Based on functionality, the data discovery market is segmented into visual data discovery, augmented data discovery, search-based data discovery, and self-service data preparation.
By application, the market segmentation consists of security & risk management, sales & marketing management, asset management, supply chain management, and others.The global data discovery market has been analyzed for five regions—North America, Europe, Asia-Pacific, the Middle East & Africa, and South America.
