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Shielding Data: Managing Insider Threats with Dataplatr & Google Cloud
February 14, 2025 in Data Analytics Management and Storage
Detect, prevent & mitigate insider threats with Dataplatr & Google Cloud. Proactive security framework for real-time monitoring & automated risk response.
Threats from Within
Data breaches are often caused by external cyberattacks, but what about threats that come from within the organization? Insider threats whether intentional or accidental can cause huge security risks as they exploit legitimate access to sensitive data. Employees, contractors or partners with access to critical systems can leak, misuse or mishandle data leading to compliance violations, reputational damage and financial loss.
With its Google Cloud Platform partnership, Dataplatr provides a proactive security framework that detects, prevents and mitigates insider risks using real-time monitoring, AI driven anomaly detection and automated response mechanisms.
Identifying & Preventing Insider Threats
Many organizations struggle to differentiate between normal employee activity and potential security risks. Traditional security measures focus on perimeter defence, but insider threats get past these defences because of legitimate access privileges. Common insider risks are:
- Unauthorized data access – Employees accessing data outside their role or downloading large amounts of sensitive information.
- Negligence & misconfigurations – Accidental sharing of confidential files, weak passwords and unsecured cloud storage.
- Malicious intent – Disgruntled employees or compromised accounts stealing or leaking data for personal gain.
As a Google Cloud partner, Dataplatr integrates strict access controls, continuous authentication and role-based permissions. By analyzing behaviour patterns Dataplatr helps detect unusual access activities so only the right people access the data.
Real-time Threat Detection & Automated Risk Mitigation
Even with access controls in place insider threats often go unnoticed until significant damage is done. Real-time monitoring and automated risk responses can help businesses detect insider threats at the earliest and prevent data loss. Dataplatr, as a Google Cloud Premier Partner, enables organizations to leverage Google Chronicle Security Operations for:
- AI driven behavioral analytics to detect abnormal user activity.
- Automated alerts and response actions to contain insider threats before escalation.
- Forensic investigation tools to track and analyze security incidents.
By combining Dataplatr’s advanced security analytics with Google Cloud’s AI driven threat detection organizations can proactively prevent data leaks and insider misuse.
Continuous Data Protection
Insider threats evolve as workforces become more hybrid and cloud driven so continuous security reinforcement becomes essential. As a Google Cloud Data Partner, Dataplatr helps businesses establish a continuous risk assessment framework by:
- Continuous access reviews to detect security gaps.
- Automated compliance enforcement to meet regulatory requirements.
- Real-time data encryption and loss prevention tools to protect sensitive files.
By automating insider threat detection and strengthening cloud security policies Dataplatr ensures continuous data protection in a constantly changing threat landscape.
Google Cloud Platform partnership, Google Cloud partner, Google Cloud Premier Partner

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The Perfect Sync: Real-Time Data Synchronization with Dataplatr & Looker
February 13, 2025 in Data Analytics Management and Storage
The Problem of Data Inconsistency
Modern businesses use multiple tools like CRMs, ERPs, marketing platforms, and financial systems to run efficiently. But when those systems don’t sync in real-time, it leads to delayed reporting, bad decision-making and operational inefficiencies.
For example, if a sales team updates customer records in a CRM but that data doesn’t sync instantly with a billing system, finance teams will process outdated invoices and revenue leaks. Lack of real-time sync creates data silos and misalignment across teams.
Dataplatr as a Looker consultant helps businesses maintain real-time data consistency by integrating Looker’s advanced BI capabilities with various systems. So, teams always work with the latest information.
Why Traditional Sync Methods Fail?
Many businesses still use batch processing or periodic data updates which means significant delays in reflecting real-time changes. When different departments work on outdated or incomplete data, it means miscommunication, operational delays and poor customer experience.
Dataplatr’s expertise in Looker consulting helps organizations move from static reports to live dashboards. By integrating Looker with real-time data streams, organizations can eliminate manual syncing delays and stakeholders can make accurate data driven decisions without waiting for overnight updates.
Real-Time Sync Across All Systems
Beyond just integrating systems, businesses need a seamless automated data sync that scales with their operations. Manual intervention, API failures or inconsistent data mapping can break workflows and give incorrect insights.
As a Looker consulting partner, Dataplatr ensures real-time data consistency across platforms by using Looker’s data modelling capabilities. That means:
- Automated data refreshes so reports reflect latest business metrics.
- Cross-system data validation to prevent mismatches and inconsistencies.
- Centralized dashboards for a single source of truth so teams can collaborate efficiently.
With this, businesses don’t have to worry about data lags, missing records or sync failures.
Scalable Data Sync
Many organizations struggle to scale real-time data sync as they grow. More tools, increased transaction volume and complex workflows make it harder to keep data unified. Through Dataplatr’s as Looker partners, helps organizations build a scalable real-time data architecture. Looker’s analytics engine allows organizations to scale by:
- Optimizing query performance for large datasets.
- Integrating with cloud storage for faster data retrieval.
- Live data monitoring to detect and fix sync issues.
With Dataplatr and Looker, businesses can sync data in real-time without sacrificing speed or accuracy. Data silos and sync delays create inefficiencies, errors and missed opportunities. Dataplatr as a Looker consultant provides businesses a real-time automated solution to sync data across all systems.

by dataplatr
Optimizing Storage and Management with Dataplatr & Snowflake’s Cloud Infrastructure
February 11, 2025 in Data Analytics Management and Storage
Companies store outdated or redundant data without realising the impact on performance and costs. Businesses using Snowflake’s cloud infrastructure get scalability and flexibility but without structured storage management they often end up paying unnecessary costs, and face performance issues like data sprawl and slow query performance. Dataplatr, as Snowflake partners, helps businesses implement structured data management so storage is optimised, performance is high, and costs are predictable.
Preventing Storage Bloat Through Lifecycle Management
One of the biggest problems that businesses face is data accumulation without governance. Historical data, redundant datasets and outdated records occupy storage and increase costs and computational overhead. Many organisations don’t have automated policies for archiving or deleting stale data.
As a Snowflake integration partner, Dataplatr helps businesses enforce automated data lifecycle policies. By using Snowflake’s Time Travel and Fail-Safe features businesses can retain data for compliance while deleting unnecessary records. Dataplatr’s approach ensures frequently accessed data is available while cold data is offloaded to cost effective storage tiers.
Structuring Data for Performance Optimisation
Storage inefficiency doesn’t just cost money – it slows queries down. When data isn’t properly partitioned or structured Snowflake has to scan large volumes of unnecessary records and that takes longer to query and costs more to compute.
Through its Snowflake partnership Dataplatr helps businesses optimise storage architecture by implementing automated clustering, micro-partitioning and efficient table structures. This means queries only retrieve relevant data, reducing computational load and speeding up performance.
Proactive Cost Control with Automated Storage Monitoring
Many businesses get unexpected cloud bills because they don’t have visibility into storage growth. Without monitoring, businesses scale storage unnecessarily and pay for unused or redundant data.
As a Snowflake partner Dataplatr integrates automated cost tracking tools that give real-time visibility into storage usage. By using Snowflake’s multi-cluster warehouse architecture businesses can dynamically allocate compute resources based on actual demand so storage scales efficiently without cost spikes.
Smarter Storage Management for Long Term Efficiency
Optimising storage in Snowflake is all about finding the balance between access, performance and cost control. Dataplatr, with Snowflake partners, helps businesses reduce storage waste, optimise queries and automate lifecycle management for long term efficiency.
Snowflake partners, Snowflake integration partner, Snowflake partnership

by dataplatr
AI-Powered Predictive Analytics for Reducing Call Abandonment Rates with Dataplatr
February 11, 2025 in Data Analytics Management and Storage
High call abandonment rates are a big problem for contact centers, resulting in lost revenue, unhappy customers and operational inefficiencies. Customers hang up due to long wait times, bad call routing and lack of proactive support leaving businesses with unresolved issues and lower scores.
Dataplatr’s contact center speech analytics takes a proactive approach using AI powered predictive analytics to detect early warning signs of abandonment and help businesses optimise staffing, routing and engagement strategies before customers disconnect.
Identify High Risk Calls in Real Time
Most contact centers struggle to identify which customers are going to abandon calls before they do. Dataplatr’s voice analytics call center solutions analyse tone, speech patterns and silence gaps to detect frustration during live interactions. By flagging high risk calls Dataplatr enables contact centers to dynamically adjust call handling strategies – whether by escalating urgent cases, triggering automated callbacks or routing customers to available agents and reduce abandonment rates before they escalate.
Predict and Prevent Customer Drop-Off
Many businesses try to address call abandonment through generic callback options or queue prioritisation but without deeper insight in customer sentiment trends these are often reactive rather than proactive.
Dataplatr’s sentiment analysis call center tools use AI to track customer sentiment in real time, identify shifts in frustration levels before a customer hangs up. By analysing repeated phrases, tone variations and stress signals Dataplatr helps contact centers implement dynamic queue management strategies – whether by offering priority routing for high-risk calls or deploying AI driven virtual assistants to answer simple queries instantly.
Optimise Agent Workflows for Faster Resolutions
A key factor driving call abandonment is slow resolution times, often due to agents doing repetitive tasks or bad routing systems. Without predictive analytics contact centers struggle to allocate resources effectively resulting in high hold times and lower agent productivity. Dataplatr’s contact center analytics services predict call volume surges and agent workload distribution. By using AI to allocate calls based on agent expertise, past resolution efficiency and real time availability businesses can reduce bottlenecks, increase first call resolution and decrease abandonment rates.
With Dataplatr’s AI powered contact center speech analytics tools you can detect customer frustration early, predict drop off risk and take proactive action to keep customers engaged. By using contact center analytics services businesses can reduce wait times, increase call resolutions and customer experience and turn drop offs into successful interactions.
contact center speech analytics, voice analytics call center, sentiment analysis call center

by dataplatr
Data Breaches and How to Protect Against Them with Dataplatr’s Google Cloud Partnerhip
February 9, 2025 in Software
Data breaches are a major threat to businesses, resulting in financial losses, reputational damage and regulatory fines. Cybercriminals exploit weak access controls, misconfigured databases and lack of real-time monitoring to get into systems and steal sensitive data. Many organizations rely on old security models that do not detect threats in real time, making them vulnerable. With its Google Cloud Platform partnership Dataplatr helps businesses secure their data infrastructure by using Google Cloud’s security tools. By combining AI-driven threat detection, zero-trust access models and encrypted storage Dataplatr keeps businesses ahead of evolving security risks.
Cloud Security Gaps
Many companies move to the cloud for scalability and performance but don’t implement strong security controls during the migration. Unprotected APIs, excessive user permissions and weak encryption create vulnerabilities that hackers can exploit. Without proper monitoring and compliance enforcement businesses risk exposing their critical data. As a Google Cloud partner Dataplatr helps organizations find and fix these security gaps. Dataplatr integrates custom security policies to comply with regulations like GDPR, HIPAA and CCPA. This proactive approach minimizes attack surfaces and strengthens overall data protection.
Real-time Threat Detection & Automated Response
Most businesses don’t have real-time threat detection, they rely on traditional security logs that only show breaches after they happen. Ransomware attacks, insider threats and API abuse often go unnoticed until damage is done. The absence of automated response mechanisms delays incident resolution even further. With its expertise as a Google Cloud Data Partners Dataplatr enables businesses to implement real-time anomaly detection, by analyzing security signals and applying machine learning-driven threat intelligence Dataplatr helps businesses detect and mitigate attacks before they escalate, ensuring business continuity.
Building a Secure, Scalable Data Architecture
Businesses need to balance scalability and security, as data grows it must remain protected. Poorly managed identity access controls, unencrypted backups and unsecured multi-cloud environments can lead to security breaches. As Google Cloud Premier Partner Dataplatr helps organizations build secure cloud architectures with role-based access controls (RBAC), automated encryption policies and intelligent threat monitoring. By embedding security into data workflows businesses can scale without compromising protection.
In today’s ever changing cyber threat landscape businesses need proactive AI-driven security solutions to protect their data. Dataplatr through its Google Cloud Platform partnership helps organizations with real-time monitoring, advanced encryption and automated threat response to mitigate risks before they escalate.

by dataplatr
Seamless Looker Integration with Tools & Platforms via APIs by Dataplatr
February 9, 2025 in Software
Businesses are relying more on analytics to make decisions, but fragmented systems and disconnected data sources are causing bottlenecks. Many organisations struggle to integrate Looker with existing platforms, resulting in data silos, inconsistent reporting and slow insights. Without seamless API based integration, teams are forced to use manual data exports, outdated reports and inefficient workflows. As a Looker consultant Dataplatr helps organisations bridge these gaps by enabling seamless API based Looker integrations with various tools, databases and cloud platforms.
Addressing API Integration Issues
Many organisations try to integrate Looker with CRMs, ERPs and marketing platforms but they face compatibility issues, inconsistent data formats and API rate limits. Poor integration means slow data refresh rates, duplicated efforts and inability to generate real time insights across departments.
Dataplatr through its Looker consulting expertise eliminates these issues by building custom API connectors and automated data pipelines. Looker’s flexible API allows businesses to pull live data from multiple sources while Dataplatr ensures structured data transformation for compatibility. This means real time dashboards that update dynamically without manual intervention.
Cross-Platform Data Flow
Disconnected data tools makes it difficult to have a single source of truth, resulting to reporting inconsistencies across departments. Teams working with finance, marketing and customer support platforms often struggle to align on shared insights due to data fragmentation.
As a Looker consulting partner Dataplatr ensures Looker integrates with cloud data warehouses, third party applications and enterprise platforms through secure, scalable API connections. By utilizing Looker’s ability to fetch, process and visualise real time data from multiple platforms, Dataplatr enables organisations to coordinate insights across all departments, reducing redundancy and improving the decision-making accuracy.
Scaling Data Operations with Integrations
API integrations must scale with business growth. Poorly optimised Looker API connections can result to slow query performance, increased API costs and data throttling issues when handling high volume of requests. By working with Looker partners Dataplatr optimises Looker’s API queries to reduce data processing and unnecessary API calls. This means as businesses grow Looker remains responsive and cost effective and users get fast real time insights without performance bottlenecks.
Seamless integration is key to unlocking Looker’s full potential. With Dataplatr as a Looker consultant businesses can connect Looker to their entire data landscape using API based solutions and eliminate silos and ensure data consistency.

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Reducing Storage Costs and Improving Performance with Dataplatr a Snowflake Partner
February 5, 2025 in Data Analytics Management and Storage
Businesses dealing with growing data face two main issues, rising storage costs and declining query performance. As data grows, cluttered storage leads to high cloud bills and slow queries delay analytics and decision making. Traditional compression methods can’t get the balance right between cost and performance and leave businesses with high overhead costs. By using Snowflake’s advanced compression techniques, Dataplatr as Snowflake partners help organisations optimise storage, reduce costs and improve query performance without compromising data integrity.
Removing Storage Bloat with Smart Compression
Many businesses unknowingly store redundant, bloated or poorly formatted data that takes up too much space. Traditional compression methods require manual tuning or result in data loss. Dataplatr, as a trusted Snowflake integration partner, helps businesses implement columnar storage and adaptive compression in Snowflake. Unlike generic compression, Snowflake dynamically selects the most efficient compression method based on data type and structure. With Dataplatr’s expertise in data partitioning, deduplication and automated clean up processes, businesses can reduce storage footprint while keeping high data accuracy.
Faster Queries without Increasing Compute Cost
Compressing data shouldn’t come at the cost of performance. Many organisations experience slow queries and increased compute time after applying generic compression. This happens when data needs to be decompressed for every query and that’s unnecessary processing overhead. With its Snowflake partnership, Dataplatr ensures businesses use Snowflake’s hybrid columnar compression to store data in a format that’s optimised for fast retrieval. By minimising unnecessary decompression and improving data indexing, Dataplatr helps organisations run high performance queries with reduced compute cost. So, analysts and data teams get results faster without needing to scale compute resources unnecessarily.
Implementing a Cost-Effective Scalable Storage Model
Storing large datasets without optimisation will cause long term scalability issues. Organisations that don’t implement tiered storage models end up paying for frequently accessed and archival data at the same rate and that’s avoidable costs. As Snowflake partner Dataplatr categorise and store data efficiently by segmenting data into hot (frequent queries), warm (periodic access) and cold (archival) tiers, businesses can make sure they’re only paying for the storage they really need and have access when they need it.
Data storage shouldn’t be a choice between cost and performance. Dataplatr, along with Snowflake partners, gives businesses the tools to remove storage bloat, speed up queries and cut cloud costs through advanced compression.

by dataplatr
Boosting Query Performance with Dataplatr a Snowflake Integration Partner
February 5, 2025 in Data Analytics Management and Storage
As more and more data are generated and analysed, slow query performance is becoming a major concern. Long query times mean delayed insights which impacts everything from operational efficiency to customer experience. Organisations using traditional data architectures struggle with inefficient query execution, resource contention and high compute costs. Dataplatr, in partnership with Snowflake integration partners, has optimisations that boost query performance. With Snowflake’s cloud native architecture and Dataplatr’s expertise, you can run queries faster, reduce costs and get real-time analytics.
Addressing Query Bottlenecks:
Many organisations face query performance issues due to poorly structured databases, inefficient indexing and resource hungry workloads. Without the right optimisations even the most powerful cloud data platforms can slow down. As Snowflake partners, Dataplatr helps businesses restructure their queries and optimise workloads to get the most out of Snowflake. By using techniques like query pruning, clustering and automated workload management, Dataplatr ensures businesses can run complex queries with zero latency. Snowflake’s dynamic compute scaling takes it to the next level by allocating resources as needed so queries don’t slow down.
Scaling Performance:
Traditional data warehouses need more compute resources to speed up queries and that means higher operational costs. Businesses need a solution that balances performance with cost. Through its Snowflake partnership, Dataplatr optimises query execution without unnecessary compute scaling. Snowflake’s intelligent caching stores frequently accessed results so you don’t have to recompute them. Dataplatr then fine tunes these processes by designing efficient data models, so you get faster performance and lower costs.
Continuous Query Optimisation:
Query optimisation requires continuous monitoring and adjustments based on changing data workloads. Businesses that don’t maintain query efficiency will see performance degrade over time. Dataplatr, as a Snowflake partner, has real-time query monitoring and performance tuning. By using Snowflake’s query profiling tools and Dataplatr’s workload management expertise, organisations get full visibility into performance metrics. This proactive approach means query execution stays optimised so you can focus on analytics not troubleshooting slow queries.
Query performance is key to getting the most out of your data. With Dataplatr and Snowflake’s optimisations, you can overcome slow query execution, reduce costs and get more out of your analytics.

by dataplatr
Data Bottlenecks to Insights: Dataplatr’s Call Center Analytics
February 4, 2025 in Data Analytics Management and Storage
Call centers handle thousands of customer interactions daily but many struggle to get meaningful insights from their data. Delayed access to real time insights, fragmented customer information and inefficient sentiment analysis creates bottlenecks that slow down operations and affects customer satisfaction. Dataplatr’s contact center analytics services solves these problems by unifying data, giving real time visibility and deeper insights into customer interactions. With Dataplatr, you can eliminate inefficiencies and turn raw data into actionable intelligence.
Unifying Data
One of the biggest problems in call centers is data fragmentation. Customer information is spread across multiple platforms like IVR systems, CRM databases and chat logs forcing agents to switch between systems to get relevant information. This wastes time and leads to inconsistent service. Dataplatr’s voice analytics call center solution solves this by bringing together data from different sources into one single dashboard. With a complete view of customer history and previous interactions, agents can respond faster, improve first call resolution and reduce customer frustration.
Understanding Customer Emotions in Real Time
A major challenge for call centers is understanding how customers feel during interactions. Traditional methods rely on keyword tracking but miss tone, pitch and emotional cues. This makes it hard for managers to identify unhappy customers and take corrective action. Dataplatr’s sentiment analysis call center provides real time insights into customer emotions. By analysing speech patterns and tone variations, agents can adjust their approach dynamically and have more empathetic conversations and higher satisfaction rates.
Using AI Powered Speech Analytics for Better Decisions
Many call centers use basic speech recognition tools that only detect keywords, missing context and intent in conversations. This limits the ability to detect trends, compliance risks and training gaps. Dataplatr’s contact center speech analytics goes beyond keyword tracking, identifying recurring customer complaints, compliance violations and agent performance issues. By providing deeper conversational insights, it empowers managers to optimise agent training, refine call scripts and ensure consistent service quality.
With Dataplatr’s call center analytics you can unite data, get real time sentiment and AI powered speech analytics that can help organisations to eliminate inefficiencies, increase customer satisfaction and equip agents with what they need to succeed.

by dataplatr
Breaking down Customer Related Bottlenecks with Dataplatrs Call Centre Analytics
January 30, 2025 in Data Analytics Management and Storage
Call centres are at the front line of customer service but bottlenecks in handling customer interactions can have a negative impact on customer satisfaction and call center efficiency. Repetitive complaints, long wait times and inconsistent responses all stem from lack of real time insights and structured workflows. These issues if left unaddressed can lead to lost customers. Dataplatr’s expertise in call centre analytics has the answer. By giving you real time insights into customer interactions Dataplatr helps call centres identify and resolve customer related blockages so you can run smoother and more satisfied.
Shorter wait times through smarter analytics:
One of the biggest customer pain points is wait times. Customers want quick resolution, but outdated systems and inefficient routing means delays. Dataplatr through its contact centre analytics services optimises call routing by analysing customer data in real time. With insights into peak call volumes, customer priorities and agent availability Dataplatr enables call centres to implement dynamic routing. This reduces wait times and gets customers to the right agent faster.
Solving repeat issues with data:
Repeat customer complaints are a clear sign of underlying issues but many call centres struggle to get to the root of the problem. These repeat interactions can waste resources and annoy customers. Dataplatr uses call centre data analytics to uncover trends in customer queries and identify repeat problems. By analysing call records and agent notes Dataplatr gives managers the data to solve these repeat issues proactively. This reduces repeat complaints and frees up agents to focus on more complex customer needs.
Better service through real time dashboards:
Customers want consistent and accurate responses but maintaining that standard is hard without the right tools. Agents don’t have real time access to the metrics that can guide their interactions. Dataplatr’s call centre metrics dashboard gives agents and managers real time visibility into key performance indicators. From live call monitoring to sentiment analysis the dashboard gives agents the insights to deliver personalised and effective solutions. By keeping agents informed during the interaction Dataplatr ensures a higher standard of service.
Customer related bottlenecks can stop a call centre from delivering smooth and satisfactory service. Dataplatr’s solutions from call centre analytics to real time dashboards help call centres fix these issues. By reducing wait times, solving repeat problems and giving agents the insights to act Dataplatr turns call centres into efficient customer focussed businesses. With Dataplatr businesses can up their service and build long term customer relationships.
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